
Built for
Fashion & Apparel
Turn Style Questions Into Confident Purchases
Help shoppers choose a fit, complete a purchase and come back for their next look. ALAbrish Technologies brings WhatsApp, Instagram, Messenger, Telegram and TikTok conversations into one inbox, with AI agents and journeys built around how people shop.
Keep good questions from becoming lost sales
Give shoppers useful answers at the moments that shape their purchase.
Make sizing less uncertain
Let AI agents explain your size charts and fit notes, then pass detailed styling or measurement questions to your team.
Find the right variant
Connect your catalog and inventory systems so shoppers can ask about colors, sizes and availability without starting a separate search.
Build a complete look
Guide shoppers toward complementary pieces based on the item, occasion and preferences they share.
Shorten the path to payment
Move from product advice to payment in chat where supported, or share a checkout link when shoppers are ready.
Handle the post-purchase questions
Use connected order data to answer delivery questions and explain return or exchange options from your store policies.
Give each drop a clear next step
Send opted-in audiences launch announcements and restock broadcasts, then handle their replies in the same workspace.
Match the conversation to the shopper's intent
Different questions need different journeys—not the same reply with a product link attached.
Give your team context, not another inbox
Manage conversations across WhatsApp, Instagram, Messenger, Telegram and TikTok in a shared workspace, with AI handling routine questions and people taking over when needed.
Keep the handoff useful
Let agents review the conversation before responding, so shoppers do not have to repeat their question.
Separate service from styling
Build routing journeys for order support, product advice and other distinct shopper needs.
Ground answers in your store
Use approved product details, care guidance and policies as the basis for AI responses.
Connect the systems behind the sale
Use 150+ integrations to bring relevant commerce and customer data into your workflows.

Build a restock journey worth replying to
Turn an unavailable size into a clear follow-up opportunity without promising stock you do not have.
- 1
Step 01
Capture the exact request
Ask which product, color and size the shopper wants, and collect permission to send an update.
- 2
Step 02
Connect availability
Use a connected inventory source or a team-managed trigger to start the journey when the variant returns.
- 3
Step 03
Send a relevant update
Notify the opted-in shopper through an eligible channel, following its messaging rules.
- 4
Step 04
Help them finish choosing
Let AI answer follow-up questions, offer a checkout route and hand over to your team if more help is needed.
See where shoppers need more confidence
Use conversation analytics and connected commerce data to improve service and refine the buying journey.
Spot recurring fit questions
Review repeated sizing concerns to identify product pages or size guides that need clearer information.
Understand launch demand
Review campaign replies and product questions to see what shoppers want to know about a new collection.
Find handoff friction
Examine where AI conversations move to your team and refine the guidance or routing behind them.
Review channel workload
Use inbox activity to understand where conversations are coming from and plan team coverage.
Improve one journey at a time
Use shopper replies and available outcome data to refine questions, follow-up timing and checkout prompts.
How ALAbrish works for fashion retail
Practical details for teams selling clothing, footwear and accessories.
Yes. Configure your AI agent to explain approved size charts, fit notes and measurement instructions rather than promise a perfect fit. It can ask clarifying questions and hand the conversation to your team when the available information is not enough.
Every conversation, one AI that never sleeps.
See how ALAbrish turns chats on five channels into revenue — in a 30-minute walkthrough.
