Yes — this is one of Elara's most natural use cases. A shopper who describes their existing wardrobe and asks for the one piece that would complete it gets exactly that: a specific recommendation with reasoning about which existing pieces it extends, how many new outfit combinations it creates, and why it earns its place rather than adding clutter. Elara is not trying to maximize basket size at the expense of decision quality — it's trying to make the right recommendation, which is what sustainable shoppers need.

Elara answers questions from your product catalog metadata. If your products have detailed descriptions, care labels, material compositions, certifications, and provenance information, Elara can answer transparency questions specifically and accurately. Enriching your catalog with this information (which most sustainable brands already have) makes Elara significantly more useful to sustainability-conscious shoppers.

Elara builds the outfit the shopper asked for — not the largest possible basket. If the right answer to "what blazer works over everything I own?" is one blazer, Elara recommends one blazer with a reason. If the shopper's brief implies a full look, Elara builds a full look. The recommendation is calibrated to the brief, not to a revenue target. This is why considered buyers trust it — and why they return.

Yes. Every Elara outfit recommendation includes a rationale for each piece: why this garment for this occasion, why this color for this shopper, why this piece works with what they already own. Sustainable shoppers who think carefully about what they buy respond well to recommendations that come with reasoning, not just a product grid.

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.