Increasing
ring saleswith AI Autocomplete
Today
- Search a word
- 191 products
- Search a word
- Pick one of 7 categories
- Scroll 26 rings
- Buy
with AI Autocomplete
- Guided search
- 3 perfect rings
- Guided search
- Targeted results
- Buy
Connected to your catalogue
Better search means shoppers find the ring they came for.
Mejuri's rings page lists 191 products behind seven category tiles and filters for material, stone and price, and leaves the narrowing to the shopper. The questions on the right run over 26 of those rings, taking them to three with attributes already printed on every card: style, stone and price. Someone who can say “gold rings, statement, with a gemstone, under $300” reaches the piece they want without scrolling a wall of results, and AI Autocomplete gets them there using your own catalogue: every choice on the right is a style, a stone or a price band your listings already carry.
Your Mejuri rings
AI Autocomplete choices
PriceUnder $300StyleStatementStoneWith a gemstoneYour catalogue becomes the vocabulary shoppers use to describe what they want.
How it works
Quick to add. Works with the search box and the catalogue you already have.
01
Connect your catalogue
Give AI Autocomplete the styles, stones, metals and prices you already print on every ring.
02
Guide shoppers as they type
AI Autocomplete predicts the detail that matters next and shows the choice inside the search box.
03
Send a richer query to your search
Pass the shopper's words and chosen attributes into your existing search, Algolia, or a custom backend.
AI Autocomplete works with your search provider.
It only takes five minutes to set up.
- Your existing search
- Algolia
- Custom search backend
The SDK
What is the AI Autocomplete SDK?
AI Autocomplete supercharges your text box. It is an SDK you drop into the search box or prompt box you already have, and it starts guiding people through what they actually meant.
The goal of AI Autocomplete is to hand a more complete phrase to the next step of your stack (your search provider or agent). It is powered by an intent layer: an action engine that pairs the reasoning of an LLM with detection that lands in 150 to 200 ms, so the guidance appears while someone is still typing rather than after they submit.
Drops into the box you have
No migration and no replatform. Your search, your models and your pipeline stay exactly where they are.
Completes the request, not the phrase
Ordinary autocomplete finishes a word. This resolves the attributes the person never said out loud, inside the box, before submit.
150 to 200 ms detection
Fast enough to keep up with typing, so the help arrives in the moment it is useful rather than a beat too late.