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AI automation and growth for e-commerce and retail.

Never run out of what sells. Never leave a customer waiting. Stores win on stock levels and speed of reply. We forecast demand, write your catalogue and handle the routine customer questions.

Built for
Founders and heads of ecommerceMerchandising and buying teamsCustomer experience and marketing leads
Sound familiar?
01Popular items sell out while slow ones sit on shelves
02Writing listings for every product takes weeks
03Order status questions fill the inbox
Step one: the hours

Where the hours come back.

Start with the repetitive work. It pays back fastest and builds trust in the system.

  • ADemand forecastPredicts what each product will sell, week by week.
  • BCatalogue writingProduct titles and descriptions written in your voice for every item.
  • CSupport agentOrder status, returns and sizing handled on chat, email and WhatsApp.
  • DReorder alertsWarns you before a product runs out or stops moving.
  • EReview repliesDrafts replies to customer reviews for you to approve.
  • FPricing signalsShows where a discount or a price change would help.
Step two: the growth

Then point them at growth.

When stock and support run themselves, you can spend your attention on finding new customers and new products.

Grow 01
Personalised recommendations

Shows each customer the products they are most likely to want, which lifts basket size.

Grow 02
New market scouting

Finds which products and regions to expand into from demand and search signals.

Grow 03
Pricing and promotion tests

Shows where a price or a promotion would lift sales without hurting margin.

What changes
Before

Popular items sell out while others sit

After

Stock follows forecast demand

Before

Every listing is written by hand

After

Listings are drafted for the whole catalogue

Before

The inbox is full of where is my order

After

Order questions are answered instantly

How it runs

In the tools you already use.

Shopify, WooCommerce and MagentoMarketplaces such as Amazon and EtsyKlaviyo and email toolsInventory and ERP systemsWhatsApp and chat
Step 1Sales history is read each night
Step 2The model predicts next weeks demand per product
Step 3You get a reorder list and alerts
Case study

94%

Weekly demand forecasts at 94 percent accuracy

Read the full story →

Representative engagement. Client name withheld under NDA. Figures are typical of results at this type of company.

Read next
Questions

Questions we hear first.

How much sales history is needed?

Twelve months or more gives useful forecasts. Less history still helps with simple stock alerts.

Can the support agent handle returns?

Yes. It follows your return policy, collects the details and passes unusual cases to your team.

Does it work with Shopify and similar platforms?

It connects to most store platforms and marketplaces that offer an API.

Start here

Let's find your first 100 hours.

Book a free audit →Free audit. Free consultation. No obligation.