Studio · Jewellery

Every piece, on a model, for every occasion.

From the product shots you already have, across your whole catalogue, on brand.

Get 3 products done free
See six looks off one product shot
48 hoursto your first three products, done
Whole catalogueone look locked, then held across every SKU
The gold panther-link necklace worn with a cream silk dress, warm daylight.

Proof

One piece. Six looks. Same necklace.

Not six products and not six models: one SKU rendered across six contexts, so you can judge the piece and the consistency in the same glance.

Proof 1 of 6: the diamond necklace with its emerald-cut blue sapphire centre stone on a deep-brown skin tone, open-collar white shirt, daylight studio.
Open collar, daylight studio
Proof 2 of 6: the same necklace on a light skin tone, grey high-neck knit, warm indoor light.
High-neck knit, warm interior
Proof 3 of 6: the same necklace on a medium skin tone, black slip dress, evening occasion.
Black slip dress, evening
Proof 4 of 6: the same necklace on an olive skin tone, navy tailored blazer, office daylight.
Tailored blazer, office
Proof 5 of 6: the same necklace on a fair skin tone, white linen shirt, outdoor daylight.
White linen, outdoor daylight
Proof 6 of 6: the diamond necklace with its emerald-cut blue sapphire centre stone in a close crop on the collarbone, showing the marquise diamond leaves and clasp detail.
Close crop, clasp detail

Same product. Same chain, same clasp, same stone. Six contexts.

A different piece, the same workflow

Drag to compare. The catalogue packshot on the left, the generated on-model image on the right.

Before: the flat packshot of the gold panther-link necklace on black, straight from the catalogue.
After: the same gold necklace generated on a model in a cream silk dress, identical frame to the packshot.
Product shotOn model

How it runs

Three steps. One workflow.

A managed workflow, not a tool you have to learn. We start by telling you which products are worth fixing first.

Step 01, catalogue audit: a ranked table of jewellery SKUs scored by imagery gap against traffic, with the top two flagged to fix first.

Occasion

One SKU, every occasion.

Jewellery does not get bought once. The same piece is merchandised differently for every moment it is worn, and the imagery has to follow.

Occasion: everyday. The diamond cluster necklace with a white tee, natural daylight.

Everyday

The version that carries the PDP.

Occasion: work. The same diamond necklace with a charcoal blazer and shirt, office light.

Work

Layered, restrained, and photographed to look it.

Occasion: evening. The same diamond necklace with a black slip dress under low warm light.

Occasion

The gifting and event story, same piece.

Straight answers

Three things you are about to ask.

Answered here rather than buried in an accordion, because they are the reasons this either works for you or does not.

Objection 01the one that matters most

“Will this look AI-generated?”

This is the question the page lives or dies on, so here is the process rather than a promise. Nothing reaches you unreviewed, and anything that misses gets fixed on a clock.

~99% output accuracyMeasured on the piece itself: chain, clasp, stone, setting.
Human review, alwaysEvery frame is checked by a person before it reaches you.
20–25 model versionsExplored before a face is locked to your brand.
72-hour fixesFlag anything and it comes back inside three days.
Objection 02consistency, not one lucky image

“Will it match my brand?”

Guidelines get locked during a 2–3 week onboarding (models, lighting, framing, crop, occasion), and then they are held for every batch after it. Two brands on the same workflow should not look like each other, and they do not.

Brand A · locked look

Brand A look 1: warm gold-toned diamond necklace, soft diffused light, close crop.
Brand A look 2: the same warm look, three-quarter turn, soft diffused light.
Brand A look 3: the same warm look, profile turn against warm bokeh.

Brand B · locked look

Brand B look 1: cool-toned diamond pendant, hard directional studio light, frontal crop.
Brand B look 2: the same cool look, slight turn, hard shadow on a grey seamless.
Brand B look 3: the same cool look, profile turn, hard studio light.
Objection 03the honest fit test

“Is this for a brand my size?”

This is a managed service built to run a catalogue, not a place to buy one image. Locking your look costs much the same whether the catalogue is small or large, so it earns its keep on depth rather than on any single shot. If that is not where your problem is, we would rather say so before it costs you a meeting.

Right fit: holding one look across every SKU is the hard part. Wrong fit: a few images before a single launch.

Scale

Built to run a catalogue, not a campaign.

The workflow already runs at volume. What that buys you is throughput you can plan a season around, not a one-off shoot you have to schedule.

4,000+brands globally
100 stylesa week, per account
48 hoursbatch turnaround
10 imagesper style, up to
10K+catalogues shipped, close to

In production now

An Indian bridal jewellery house runs separate guidelines per occasion and publishes the output straight into Shopify metafields.

  • One guideline set per occasion
  • Published to Shopify metafields
  • Held consistent across every batch

Get 3 products done free.

Send us your store. We come back in 48 hours with 3 products done: on a model, in context, from the shots you already have.

  • Three of your own products, not a showreel
  • A catalogue audit before the first call
  • Human review on every frame you see

Send us your store. We come back in 48 hours with 3 products done.

Get 3 products done free

Three fields. The store URL is what lets us audit your catalogue before the first call.

Add your store. A bare domain like yourbrand.com is fine.
Add your name.
Add a work email we can send the samples to.

No call required to see the samples.

Got it. We'll send three products back within 48 hours.

Next: we run a quick audit of your catalogue, pick the three products with the widest imagery gap, and render them on a model in context.

The reply comes from the Studio team at whatmore.ai. Worth allowlisting the domain now so it doesn't land unrecognised in spam.