Yes. Elara reasons about age appropriateness from the brief the shopper provides. A parent asking for a 6-year-old's party outfit gets different recommendations from a 15-year-old asking for a prom look — the catalog items, the silhouettes, and the rationale all adjust to the stated age and context. If your catalog covers both age ranges, Elara draws from the appropriate section for each brief.

Elara answers sizing questions from your specific product metadata. If your catalog includes height/weight sizing guides, fit character notes (relaxed vs. slim, runs large vs. small), and fabric behavior notes (does this stretch?), Elara uses all of it to give a specific sizing recommendation for a child with the dimensions the parent provides. Generic size charts are replaced with product-specific fit guidance.

Yes. The conversational interface works for self-purchasing teenagers as naturally as it works for parents. A 14-year-old asking "I need something for my friend's birthday, I want it to feel like my style but also be party-appropriate" gets an outfit recommendation that balances both priorities. The Style Graph builds her taste model over time, so return visits become more accurate to her personal aesthetic.

Yes. Girls' fashion occasion dressing is globally diverse — Eid outfits, Diwali looks, cultural celebrations, religious ceremonies, school events. Elara takes the occasion description in natural language ("something for my daughter's Eid — she's 9, she likes bright colors") and reasons about what that occasion implies in terms of formality, cultural appropriateness, and aesthetic. Catalog richness (occasion metadata on products) sharpens these recommendations.

Yes. The SDK works with Hydrogen and any front end that can load a script or call the API.

Your catalog, stock and anonymous on-site behaviour. No personal data is required to style a shopper; nothing is shared across brands or used to train models for anyone else.