Does the AI render rings on the correct finger?

Yes. Photta detects the shopper's hand orientation and finger position from the photo, then places the ring on the most likely intended finger (default: ring finger of the visible hand). The shopper can swap fingers with one tap.

How accurate is the stone color and brilliance?

Photta preserves the color and brilliance from your product photo. A diamond's sparkle, a sapphire's depth, a morganite's blush — all carry over. We don't apply any color correction that would mislead the shopper about the actual stone.

Can shoppers try multiple rings stacked together?

Yes. The widget supports stacking — shoppers can add a second or third ring to visualize how their stack would look. Particularly useful for bridal stacks (engagement + eternity + wedding band).

Will it work for unusual earring styles like ear cuffs and ear climbers?

Yes. The face-landmark detection identifies the full ear shape, so the AI renders cuffs along the helix, climbers up the ear, and traditional studs on the lobe — each anatomically correct.

How are the photos protected?

Shopper photos delete within one hour of upload. Generated try-on images delete within 24 hours. We never share, sell, or train AI models on shopper photos. GDPR + CCPA compliant by default.

Does it work for unisex or men's jewelry?

Yes. The AI is trained across hand sizes and shapes for all gender presentations. Men's chains, signet rings, and watches (style-only — not for sizing accuracy on watches) all render correctly.

For jewelry brands

The virtual try-on widget for online jewelry

Photta lets shoppers see your rings on their hand, necklaces on their neckline, and earrings on their face — before they buy. Designed for fine, fashion, and bridal jewelry brands.

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Jewelry returns hide a different problem

Jewelry returns aren't usually about size — they're about how the piece looks on the shopper. A ring that's stunning in a product shot can feel wrong on a hand. A delicate necklace can disappear on the neckline. Photta lets shoppers verify the visual fit on their own body before they commit.

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Hand and face rendering
Specialized AI for jewelry: rings render on the shopper's hand, necklaces on the neckline, earrings on the face. Each anatomically correct, each photo-realistic.
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Closes the styling gap
Online jewelry conversion suffers because shoppers can't verify the look. Photta lifts conversion 18–25% on fine jewelry, 30%+ on statement pieces.
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Built for social-share moments
Shoppers want to show their friends ('does this necklace look good?'). The try-on result is share-friendly — many jewelry brands report direct social-driven traffic from try-on screenshots.
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Cuts costly returns
Fine jewelry has high handling costs per return. Cutting return rates 20–25% on a $400-AOV brand recovers significant margin.

Backed by jewelry industry numbers

+22%: Avg jewelry conversion lift
−24%: Photta cohort return reduction
💍: Hand / face / neck rendering
29: Languages supported

How shoppers experience Photta on a jewelry page

1
Tap 'Try it on'
Photta sits on your jewelry product page. The shopper opens it and snaps a photo — hand for rings, face for earrings, neckline for necklaces.
2
AI renders the piece
About 10 seconds later: the shopper sees the jewelry on their actual body part. Stone color, metal tone, scale, and drape all render accurately.
3
Add to cart with confidence
From the try-on result, the shopper picks the metal/stone variant and adds to cart. Conversion lift is highest on $200+ pieces.

Jewelry brand use cases

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Fine jewelry brand

$500+ AOV fine jewelry brands use Photta to remove the high-stakes uncertainty. Shoppers buy with confidence; returns drop sharply on engagement-adjacent pieces.

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Costume / fashion jewelry

$30–$80 AOV fashion jewelry wins on volume conversion lift. Shoppers add multiple pieces because they can verify the layered look.

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Bridal jewelry

Bridal sets (engagement, eternity, wedding band) require previewing how the stack will look. Photta renders the full stack on the bride's actual hand.

Built for jewelry shopping

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Hand pose detection

AI detects the shopper's hand orientation and finger position. Rings render on the correct finger at the correct angle, every time.

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Face landmark detection

For earrings: AI locates earlobes, jawline, and hair to render earrings naturally — no awkward floating jewelry.

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Stone and metal accurate

Diamond brilliance, gold warmth, silver coolness, gemstone color — all preserved from product photo to try-on.

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Scale-correct

A 3mm stud and a 30mm chandelier earring render at the correct relative size on the shopper's face. Critical for premium jewelry.

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Privacy-first

Photos delete in under one hour. Particularly important for face / hand close-ups.

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Per-piece conversion analytics

See which jewelry pieces convert best after a try-on. Use the data for homepage merchandising and limited-edition release planning.

Jewelry brand FAQ

: Yes. Photta detects the shopper's hand orientation and finger position from the photo, then places the ring on the most likely intended finger (default: ring finger of the visible hand). The shopper can swap fingers with one tap.

Pricing for jewelry brands

Three tiers from $49/mo. 14-day free trial, no credit card required.

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Ship virtual try-on for your jewelry catalog

30 seconds to install. 14 days free. Lift conversion on every product page.

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