Sizing that remembers every measurement.
SizeMemo connects your garment measurements, size charts and return feedback, so you can recommend sizes from real numbers and catch products that don't fit like the rest of your range.
Shopper usually wears L. Linden's chest measures 5 cm narrower than the brand's shirt block.
| POM | Garment | Body | Ease | Target |
|---|---|---|---|---|
| Chest | 110.5 | 100 | +10.5 | 9–15 ✓ |
| Waist | 106 | 88 | +18 | 10–18 ✓ |
| Sleeve | 67 | 63 | +4 | −1–2.5 · long |
The answers are already in your tech packs and your returns.
A shirt from a new factory comes in a little narrow. Nobody notices until the returns arrive, and the comments say the same thing in a hundred different ways: tight across the chest, buttons pull, runs small.
SizeMemo reads those comments, groups them into fit categories, and lays them next to the garment's measured specification. When both say the same thing, your fit team gets one clear, evidenced flag.
Five capabilities, one source of measurement truth.
Garment measurement intelligence
Store every point of measure for every size. Compare products, sizes and categories against your brand blocks, with a full edit history.
Fit recommendation engine
Deterministic size matching from garment measurements and a shopper's own measurements, fit preference, or a garment they already own.
Return feedback analysis
AI classifies free-text return reasons into too small, too large, too long, too short or unexpected fit — with a human review queue.
Size consistency monitoring
Flags products whose measurements drift from your established sizing, and checks whether customer feedback agrees.
Fit insights dashboard
Return rates by product and size, fit-issue patterns by category, and exportable reports for production meetings.
Built for honesty
Every recommendation shows its working and its confidence. No body scanning, no black box, no invented precision.
Arithmetic first. AI second.
Measure the garment
Your team records chest, waist, hip, lengths and more for every size, against the block it was graded from.
Compare with the shopper
Garment minus body gives the ease at each point. Each size is scored against the ease range for the shopper's fit preference. The lowest score wins.
Explain it plainly
Amazon Bedrock turns the finished calculation into a short, readable explanation. It never picks the size or changes the numbers.
We don't measure bodies from photographs.
SizeMemo uses measurements that shoppers enter themselves, or a garment they already own. It does not estimate body measurements from photos, and it will not do so unless a validated, consent-based measurement system is in place.
Recommendations are guidance. Self-measurement varies by a centimetre or two, fabrics behave differently, and taste is personal — so every result carries a confidence level and says when a shopper is between sizes.
See your own range through SizeMemo.
Bring a size chart and a returns export. We'll walk through what the measurements and the comments are telling you.
Request a demo