Lead generation
Turn style searches into shoppers
AI matches a shopper's look and values to your pieces and points them to your boutique.
Fashion shoppers search by feeling as much as by item — a sustainable linen dress, minimalist workwear, a wedding-guest look under budget — and the boutique whose pieces surface is the one they come to. This workflow lets an AI agent match that request against the collection you have described and put a small, on-point selection in front of the shopper, so a style search finds you instead of scrolling past.
Last reviewed
Can AI find pieces from my boutique for a specific look?
It can, if you have described the collection and what it stands for. The agent reads a request like “sustainable linen, wedding guest, under 200” against your pieces, your materials and your values, and returns a small curated selection rather than a catalog dump.
- Answers
- Your collection, materials and values
- Hands over
- A curated selection and the brief
- Not yet
- Selling the piece
Your customers are already asking AI
These are the kinds of prompts people now type into an AI assistant — the demand this workflow is built to serve.
“find a sustainable brand for a linen summer dress”
“where can I buy a wedding guest outfit under 200”
“find a boutique with minimalist workwear”
“who sells handmade leather bags in my area”
So how does a customer's AI find this at all?
Shoppers only come to the pieces they discover — and that discovery now happens through an assistant. Make your collection and this style finder available to AI, so when someone asks their assistant to find a look or a brand like yours, AI can point them to your pieces and start the conversation.
You describe your pieces, your materials, your sizing and what your boutique stands for — and Fugentic publishes that as an MCP server: the thing that lets an AI assistant ask your boutique a question and get a real answer back. It is registered from the platform, so an agent finder, the index an assistant checks to see what is available, can pick it up.
Then someone searching by feeling — minimalist workwear, a sustainable brand, a wedding-guest look on a budget — gets your pieces judged on the things you actually chose them for. A boutique’s whole advantage is taste, and taste has to be described before it can be matched.
- 1You describe what you sell
- 2It's published and registered
- 3A customer's assistant asks
- 4It answers in your words
- 5The details reach you
What AI can and cannot do here today
What AI can do today
- It can describe your pieces, your materials, your sizing and what your boutique stands for.
- It can match a request on values as well as items — sustainable, handmade, made in Europe — where you have described them.
- It can return a short curated selection and hand you what the shopper was looking for.
What it cannot do yet
- It cannot sell the piece. It brings the shopper to it; the purchase happens the way it already does.
- It cannot confirm a size is in stock. It works from your described collection, not from a real-time inventory count.
Everything on the left is what a text-based setup supports today. Quoting against live data, and taking the booking itself, need server types we hope to add later.
How the AI style finder workflow works
- 1
Shopper describes the look
A customer asks for a piece, style, or brand ethos via chat or DM.
- 2
AI matches your collection
The agent matches the request against the collection you have described — the pieces, the materials and the ethos behind them.
- 3
Selection curated
The agent pulls together a small, on-point selection worth showing.
- 4
Pieces put in front of the shopper
The shopper gets the curated selection and where to find it: your boutique, your pieces.
Tools in this workflow
These are the tools the workflow touches. Map them in the Agentic Planner to describe what your agent can do.
Industries this fits
Build this workflow
Open this exact workflow in the free Agentic Planner and adapt it to your business — no code required.
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Frequently asked questions
Yes — if your pieces are tagged with materials and ethos, the agent can match on them, not just item type.
It matches on the sizes and variants you have described. For whether a particular piece is on the rail today, it points the shopper to you rather than guessing.
Yes — the agent can send the curated selection by email so the shopper can come back to it.
Because taste does not survive a keyword search. Fugentic publishes what your pieces are and what they stand for as an agent an assistant can ask, then registers it so an agent finder — the index an assistant checks to see what is available — can pick it up. An assistant matching “minimalist, sustainable, under 200” needs a boutique that can answer on all three.
Make your services available to AI
Describe what you sell, what it costs and how you decide — then publish it as an agent an assistant can ask. No code.