Retail AI automation for the tickets, listings and returns someone has to read.
Tickets, supplier sheets and return requests, drafted for your team to approve.
Your store platform already handles the mechanical parts: orders, labels, inventory counts. What it cannot do is read a customer email and work out what they want, turn a supplier spreadsheet into a product page, or decide whether a return is routine. We build AI that does the first pass on that work, and your team approves what goes out.
- Free
- AI audit before you commit to anything
- Fixed price
- Builds quoted against a defined scope
- Human approval
- On replies, refunds and anything published to your store
The work your store platform cannot do for you
Every ticket gets read from scratch
Where is my order, can I swap the size, the item arrived damaged. Your support team reads each message, looks up the order in another tab and types an answer that is mostly the same as the last fifty.
Supplier data is not a product page
New stock arrives with a spreadsheet of SKUs, dimensions and a line of manufacturer copy. Someone has to turn each row into a title, a description, tags and filter attributes before it can go live.
Returns that do not fit the policy
Most returns are routine. The ones outside the window, missing a receipt or claiming damage each need someone to read the history and make a call, and they sit in a queue until someone does.
What we build for retailers and ecommerce brands
Each of these is a real engagement shape. Open one to see how it works, what it needs from you, and where a person stays in the loop.
Any figures are targets we scope towards, not guarantees. What you actually get depends on your volume, your systems, and how much stays under human review.
Support ticket triage and drafted replies
Customer emails and chats pile up in the helpdesk, and agents spend most of their time on order-status and policy questions they have answered many times before.
Support ticket triage and drafted replies
Customer emails and chats pile up in the helpdesk, and agents spend most of their time on order-status and policy questions they have answered many times before.Each new ticket is read, tagged by intent and urgency, and matched to the customer's order. The AI drafts a reply from the order data and your written policies. Agents edit or approve the draft, and anything angry, unusual or high-value goes to the top of the queue.
How it works
- 01Connect your helpdesk and store platform so each ticket can be matched to its order
- 02Write down your shipping, exchange and return policies in a form the AI can use
- 03Classify incoming tickets by intent, urgency and sentiment
- 04Draft a reply that uses the real order status and your policy wording
- 05Hold every draft in the helpdesk for an agent to edit and send
Where a person stays in the loop
The AI drafts and an agent sends. Nothing goes to a customer without a person reading it first, unless you later choose to let a narrow category, such as tracking-link replies, go out on its own.
- Agents approve or edit every draft before it is sent
- Refunds, credits and discount codes always need a person
- Complaints and chargeback threats are flagged, never answered automatically
What it needs from you
- Your helpdesk (Gorgias, Zendesk or a shared inbox) with API access
- Order lookup from your store platform
- Your current policies and a sample of past tickets and replies
Common questions
- Will customers know they are talking to AI?
- In this setup they are not talking to AI. They get a reply from your agent, who used an AI draft to write it. If you want a customer-facing assistant instead, that is a separate build with its own disclosure decisions.
Typical build: 2 to 3 weeks·Aim: Agents spend their time on the hard tickets
Talk through this oneProduct description and catalog enrichment
Supplier spreadsheets and PDFs have the facts but not the copy, and filling in titles, descriptions, tags and variant attributes by hand holds new products back.
Product description and catalog enrichment
Supplier spreadsheets and PDFs have the facts but not the copy, and filling in titles, descriptions, tags and variant attributes by hand holds new products back.The AI reads supplier data and drafts product titles, descriptions, tags and filter attributes in your brand voice and naming rules. Drafts land as unpublished products or a review sheet, and a merchandiser approves them before anything goes live.
How it works
- 01Collect a set of your best existing product pages as the style reference
- 02Read supplier spreadsheets, PDFs and spec sheets for each new SKU
- 03Draft titles, descriptions, tags and attributes such as material, size and color
- 04Flag missing or conflicting supplier data instead of guessing
- 05Create the products as drafts for a merchandiser to approve and publish
Where a person stays in the loop
Nothing is published automatically. The AI writes drafts and points out where the supplier data was thin; your team decides what goes live.
- Every product stays in draft until a person publishes it
- Claims about materials, safety or sizing are checked against the supplier source
What it needs from you
- Store platform API access (Shopify, WooCommerce, BigCommerce or Lightspeed)
- Supplier data files in their usual format
- Examples of product pages you consider right
Typical build: 2 to 3 weeks·Aim: Consistent attributes across the catalog
Talk through this oneReturns and exception handling
Return requests outside the normal rules need someone to read the message, check the order history and decide, and those decisions are inconsistent from one person to the next.
Returns and exception handling
Return requests outside the normal rules need someone to read the message, check the order history and decide, and those decisions are inconsistent from one person to the next.The AI reads each return or exception request, checks it against your policy and the customer's order history, and sorts it: routine, needs a decision, or likely abuse. For the ones that need a decision it writes a short summary and a suggested outcome for a person to accept or change.
How it works
- 01Read return requests from your returns portal, helpdesk or email
- 02Pull the order, shipping and past-return history for that customer
- 03Compare the request with your written return policy
- 04Sort it as routine, needs review or possible abuse, with the reason
- 05Queue reviewed cases with a summary and suggested outcome for staff
Where a person stays in the loop
Refunds and denials are decided by your staff. The AI does the reading and lays out the facts so the decision takes less time.
- Every refund, store credit or denial is approved by a person
- Abuse flags are suggestions for review, never automatic denials
What it needs from you
- Access to returns data (your returns app, helpdesk or order notes)
- Your return and exchange policy, including the unwritten exceptions
Typical build: 3 to 4 weeks·Aim: Exceptions decided in one place
Talk through this oneDemand and reorder flags
Reorder decisions are made from gut feel or a spreadsheet someone updates on Fridays, so fast sellers stock out and slow ones tie up cash.
Demand and reorder flags
Reorder decisions are made from gut feel or a spreadsheet someone updates on Fridays, so fast sellers stock out and slow ones tie up cash.Sales, stock and open purchase order data is pulled together every week. The AI flags items that are selling faster or slower than usual and suggests reorder quantities, with a plain-language note on why. Your buyer decides what to order.
How it works
- 01Pull sales and inventory data from your POS and store platform
- 02Add open purchase orders and supplier lead times
- 03Flag items whose sales pace has changed or that will run out before the next delivery
- 04Send the buyer a weekly list with suggested quantities and the reason for each
What it needs from you
- Sales and inventory data from Shopify, Square, Lightspeed or a similar system
- Supplier lead times, even rough ones
Typical build: 2 to 3 weeks·Aim: One weekly reorder list with reasons
Talk through this oneBuilt inside your systems, not beside them.
We work in your cloud, using your tools, under least-privilege access. We never train models on your data, and you keep the source code.
No card data handled
Card numbers stay with your payment processor. Our systems never receive or store them.
Least-privilege access
Each workflow gets only the store and helpdesk permissions it needs, scoped to its job.
Human approval
Replies, refunds and published product changes wait for a person to approve them.
Audit trail
Every AI draft, classification and human approval is logged.
Systems we build around
- Shopify
- WooCommerce
- BigCommerce
- Square
- Lightspeed
- Gorgias
- Zendesk
- Klaviyo
- ShipStation
These are systems retailers commonly ask about, not a list of existing integrations. We connect where your system offers an API or a reliable export, and confirm what your plan allows during scoping.
Questions we get
What is AI automation for retail businesses?
Retail AI automation is software that handles the reading and judgement work in a store: understanding customer emails, turning supplier data into product listings, sorting return requests and spotting changes in demand. It differs from rules-based retail business process automation, which moves orders and data between systems but cannot interpret a message. In what we build, the AI drafts and staff approve.
Which retail and ecommerce processes can AI automate?
The best fits are high-volume tasks that need reading: customer service triage and reply drafts, product descriptions and attributes from supplier files, return and exception review, and reorder suggestions from sales data. Pricing strategy, buying decisions and refunds stay with your team. AI automation for retail operations works best when it prepares those decisions rather than making them.
Does AI automation integrate with our POS or inventory system?
Usually, yes, where the system has an API or a reliable export. Shopify, WooCommerce, BigCommerce, Square and Lightspeed all offer APIs, but what you can reach depends on your plan and the apps you already run. During scoping we check the access your account actually has and tell you before quoting if anything is limited.
How much does AI automation cost for a retail or ecommerce business?
It depends on how many workflows are in scope, your ticket and order volume, and how much judgement the AI has to replicate. The AI audit is free and ends with a scoped estimate. Builds are fixed-price against that scope, and ongoing support is a flat monthly fee covering hosting, monitoring and model costs. Our pricing page explains what moves the number.
Can AI automate order processing and customer service?
It can take on the parts that need reading. Your store platform and tools like ShipStation already handle routine order processing. AI adds value on the exceptions: address problems, split shipments and customer messages that need interpreting. For customer service, it classifies tickets and drafts replies from the order data, and an agent approves each one before it is sent.
What's the ROI of AI automation for a retail operation?
Return comes from support hours given back, new products going live sooner, more consistent return decisions and fewer stockouts. How large it is depends on your volume and how manual the work is today. The free audit measures your current process first, so any estimate is based on your numbers rather than an industry average.
How long does implementation take?
Most builds go live in two to three weeks from a defined scope. Work that touches several systems, or a platform with restricted API access, can take longer. With AI automation for ecommerce businesses we usually start with one workflow, often support triage or catalog enrichment, prove it on real tickets or products, and then add the next.
Will AI automation replace retail or customer service staff?
That is not what we build it for. The AI takes the repetitive reading and first drafts, so your team spends its time on upset customers, judgement calls and the store itself. Every workflow we build keeps a person approving replies, refunds and anything published to your storefront.
Is retail AI automation secure for customer and payment data?
Yes, and payment data stays out of it entirely. Card numbers remain with your payment processor and never pass through our systems. For customer names, addresses and order history we use least-privilege access, encrypt data in transit and at rest, and log every action. We never train models on your data, and you keep the source code.
Find the queue your team reads through every day.
Book a scoping call. We will look at your support inbox, catalog backlog and returns with you, tell you which one AI can take the first pass on, and what it would cost.
Book a scoping call