Category-aware pilots
Launch separate acceptance criteria for sarees, kurtis, complete festive outfits, and jewellery.
AI virtual try-on workflows for saree, kurti, lehenga, jewellery, boutique, and Indian D2C fashion ecommerce catalogs.

An Indian fashion store can add a photo-based try-on action to eligible saree, kurti, lehenga, jewellery, and other wearable product pages. The store's backend securely sends the customer and product images to TryRobe, receives an asynchronous result, and presents it with normal fabric, measurements, blouse, size, and return information.
Indian garments often contain detailed borders, embroidery, motifs, drape, coordinating pieces, and jewellery. A careful catalog-image standard and category-specific quality review are therefore more valuable than enabling every SKU immediately.
Launch separate acceptance criteria for sarees, kurtis, complete festive outfits, and jewellery.
Use manual Business credits or the Small plan rather than committing to enterprise volume.
Keep secret keys server-side and exclude private customer images from search and analytics payloads.
No. Start with categories and images that meet clear quality standards, then expand using real completion and support data.
No AI preview can guarantee exact fabric physics, drape, sheen, or embroidery placement. Keep real catalog photos and descriptions prominent.
Yes. A developer or ecommerce agency can connect the boutique's backend to TryRobe without exposing the license key in the browser.
Start with one complimentary standard generation or create a Business workspace for API access.