The AI assistant for product-led fashion retailers
Every product decision, optimised. From range planning and supplier audits to fit, depth of buy, size curves and pricing — AI uniquely tuned to your business.
Maeve takes teams beyond Excel, freeing up time to think creatively and solve the problems that matter.
Ask Maeve anything
Returns, fit, sizing, revenue — your data, in plain English.
Many signals.
One decision.
Your data lives everywhere — Shopify, the warehouse, the PLM, the review tool, the customer-care inbox. Maeve reads all of it. Then it tells you the needlemovers for this week.
- Connects to Shopify, your warehouse, PLM, reviews, and ticket data — out of the box.
- Models the revenue impact of every recommendation, before you act on it.
- Drafts the next step — a re-grade, a Shopify edit, a Slack update — in one click.
Catch the £870k
mistake before it ships.
Maeve reads your PLM data the moment a product is drafted. It compares the spec to every comparable item you've ever sold — and tells you, with a number, what the next launch is going to cost you in returns.
- Pre-launch risk score with a forecast return rate range.
- Compares against historical performance of comparable styles.
- Drafts the listing copy and pushes straight into Shopify.
Pre-launch risk · medium
Based on returns data from 14 comparable knit styles, this product has a forecast return rate of 34–39%. The dominant risk is sleeve length on the block.
Every product. Every metric. Searchable in plain English.
Stop building dashboards. Filter your entire catalogue by anything Maeve knows — return rate, sell-through, fit feedback, review sentiment, margin — and act on what matters.
- Saved filters for your team — "Returns trending up", "New launches", "Knitwear in red".
- Click any row to drop into a Maeve thread already scoped to that product.
- Export to CSV, share to Teams, or push to a Shopify segment.
| Product | Category | Net sales · 90d | Return rate | Flags |
|---|---|---|---|---|
| Mira Cardigan | Knitwear | £142k | 41.2% ↑ | Returns ↑New |
| Otto Linen Shirt | Shirts | £98k | 36.4% ↑ | Returns ↑ |
| Atlas Jeans 32W | Denim | £74k | 32.0% | Fit ↻ |
| Eira Knit Jumper | Knitwear | £61k | 29.1% ↓ | |
| Linen Co-ord Set | Sets | £58k | 27.4% ↓ | Improving |
| Ridge Field Jacket | Outerwear | £52k | 14.2% ↓ | Top performer |
| Suri Slip Dress | Dresses | £44k | 22.8% |
Why is this product returning? Now you can actually find out.
Every SKU has a page that reads like a brief, not a dashboard. Sales, returns, fit reasons, customer photos, AI insight — and a one-click route to ask Maeve about it.
- Customer fit photos surfaced automatically from reviews.
- Top return reasons mined from reviews, ticket comments, and surveys.
- Notes you and your team leave stay attached to the product forever.
The weekly trade meeting,
written for you.
Every Monday morning Maeve writes a Monthly and Weekly trade report from your live data: what sold, what returned, what changed, what to do this week. No more half-day pulls; no more arguing about which sheet is current.
- Monthly + Weekly reports generated automatically from Cube — never out of date.
- Comments and action items thread inline; assign and resolve from the report.
- One-click share to Teams, Slack or PDF — branded for your retailer review.
Week 17 · in three numbers
Knitwear drove the gain — net revenue up 14% WoW on the back of the Mira Cardigan re-grade landing on shelf. Returns on the line are still 3.4pt above category average; the sleeve fix is clearing slowly.
Watch for next week: the Atlas Jeans 32W block ships Wednesday — model says −£14k weekly impact if we don't update the size guide before launch. Phoebe owns.
What our customers are saying.
"We've really changed our strategy from the data we've got from Maeve. Maeve takes a lot of that time away from our internal teams, whether it be customer care or production teams. The beauty around Maeve is the fact that they can take all our unstructured data and put it all together."
Questions we get
at every demo.
To see the product in action, or get answers to other questions, book a demo.
- We connect to your existing systems — Shopify, returns, reviews and PLM (where you have them). Within 12 hours, our models have built a full picture of your business. From there you can chat with Maeve in plain English, browse styles by performance, score new launches before they ship, and get weekly reports that surface what to act on first.
- Very quickly. If a brand is on Shopify, setup can take around 30 minutes, and insights start appearing immediately once the data is connected. One of our best results so far is a 16% reduction in returns.
- Pricing starts from £1k per month for brands under £10m in annual revenue. Book a demo for a detailed quote.
- Every brand is different — when we start working together, we’ll see your unique fingerprint. Some changes will be instant, and we can help automate these; some will be slower, like grading revisits, pricing strategy review and range planning for profitability updates.
- We love working with our customers really closely, and are in our London retailers’ offices at least once a week. There’s no limit on the number of users on the tool, so your whole team can access as much as you like — and ping us anytime you need help. Formal time together will depend on contract — you should be able to self-serve.
- We typically connect to: sales systems (e.g. Shopify), returns platforms, PLM systems (or Excel files), reviews and customer service tools. The more data sources connected, the more accurate the insights.
- Maeve runs entirely in the EU on AWS (Stockholm), with TLS 1.2+ in transit and AES-256 at rest. Multi-tenant isolation is enforced at the infrastructure level, so brands never see each other’s data. Auth0 handles authentication — we never store passwords. We’re GDPR-compliant as your data processor, with a 72-hour incident notification policy. Full details on our security page.
- Fashion doesn't have a revenue problem — it has a profit leakage problem. The biggest causes are returns, unknown fit issues, supplier quality problems, exploitative customers, and premature discounting. Thousands of small product decisions go slightly wrong, and that's what eats margins.
- An AI size recommendation costs roughly 0.4g CO₂ in compute energy, while the return it helps avoid generates an estimated 300g–2kg CO₂ in van logistics alone — more if the item is ultimately destroyed. The biggest sustainability win in fashion is simply making products customers keep.
Stop drowning in Excel files.
Start collaborating with Maeve.
30-minute walkthrough. Bring your questions — we'll show you how Maeve works, where it earns its keep, and what it could mean for your team.