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FAQ’s: SPREEAI Photorealistic Try-On

Note: This FAQ is designed to complement the Getting Started Guide and the Integration Overview. It addresses the most common questions we hear from new and existing partners about asset preparation, timelines, quality control, support, and scalability. If your question isn’t covered here, your dedicated SPREEAI support contact can provide direct guidance.

Q1: What types of garment assets does SPREEAI require for the try-on?​

A: SPREEAI works with high-quality digital assets of your products. Partners typically provide garment images (front view, and back view if available) on a clean background, with the garment well-lit and free of obstructions. For the authoritative resolution, file size, and format specifications, see Garment Image Requirements. Currently supported categories include most tops, bottoms, and form-fitting dresses, with more (outerwear, patterned fabrics, etc.) expanding as the technology evolves. Detailed asset guidelines (lighting, angles, file naming) are provided to ensure accuracy. If you have 3D models, discuss with our team — while the pipeline is built for 2D, we can explore leveraging 3D assets if appropriate.

Q2: How long does it take to get our products enabled for try-on?​

A: Timelines vary based on volume and complexity. Initial setup (account creation, asset gathering) typically takes about a week on the partner’s side. Once garment images are submitted, our processing pipeline usually prepares try-ons within 1 business day per item. For a pilot with ~50 garments, the first batch of try-ons is often ready within 1 week. Integration and testing on your staging site/app adds another week. In total, most partners reach live pilot launch within 2–3 weeks. For ongoing additions, new batches of ~50 garments can usually be processed and live within 12–24 hours.

Q3: What quality control measures are in place for the try-on images?​

A: Quality is our top priority. Every try-on render undergoes automated checks to detect visual artifacts and misalignments, followed by manual QA on sample sets. We compare outputs with reference product photos to verify accuracy of colors, fabrics, and prints. Any image that doesn’t meet standards is flagged and reprocessed. By the time a try-on goes live, it has passed strict visual and functional quality gates.

Q4: Can we request revisions if a try-on output isn’t satisfactory?​

A: Yes. During pilots, we encourage partners to review outputs and share feedback. If adjustments are needed — for example, a print alignment or garment drape — our team will refine and reprocess. Typically, one to two rounds of revisions are included in the pilot scope. Post-launch, revision requests can still be submitted via support or your partnership manager, with turnaround usually a few days depending on complexity.

Q5: What support does SPREEAI provide during integration?​

A: Every partner has access to integration documentation, sample code, and a dedicated support channel. For most pilots, we assign an integration engineer or success manager to guide setup. Enterprise partners receive regular check-ins and custom integration planning. We also offer technical discovery calls, assistance with SDK installation, API authentication, and troubleshooting. Our support can scale from self-serve to white-glove depending on your needs.

Q6: In what formats or specifications should we provide our product assets?​

A: Each garment should be photographed front-on against a clean background, with optional back or side views for complex items. Consistent lighting and angles across products improve realism. File naming with SKUs or IDs is recommended but not required if you use a PIM/DAM system. For accepted formats, resolution, and file size, see Garment Image Requirements. 3D models are not required; the AI generates photorealistic try-ons from 2D imagery.

Q7: Is there a dashboard to track usage and performance of the photorealistic try-on?​

A: A Partner Dashboard is currently in development and will provide visibility into garment processing, readiness, and try-on performance. Once live, it will allow partners to track key metrics such as try-on sessions, engagement rates, and add-to-cart conversions, with additional analytics to be added over time. In the meantime, our team provides usage and performance reports directly and can share data extracts or custom reporting as needed.

Q8: Can SPREEAI handle large scale — hundreds of products or millions of try-ons?​

Yes. SPREEAI is designed to scale with your business. Our systems can support large product catalogs and high volumes of try-ons, with infrastructure that adapts to demand. We also work with partners ahead of major launches to make sure capacity aligns with expected traffic.