Our client is a high-growth fashion-tech startup specializing in AI-driven virtual try-on (VTO) solutions. The company enables brands to generate high-quality, on-model content from a single product image, effectively eliminating the need for expensive conventional shoot dependencies. By fitting new products onto existing model assets (AI-generated), the company helps clients cut content production costs by up to 80%, accelerate time-to-market without compromising visual quality, and support high-volume catalog needs.
The project required high-precision retouching support to correct the limitations of virtual try-on AI and prepare the images for brand use. Each image had to match the actual product exactly while preserving natural fit, texture, accessories, and model presentation across a large fashion catalog. Because the scope covered multiple apparel and accessory categories, every image had to follow category-specific correction standards. The primary objective was to eliminate "AI hallucinations" while maintaining 100% product accuracy across diverse model iterations.
Although the source visuals were AI-generated, the final outputs had to perform like brand-ready fashion assets. The main challenge was maintaining product-level precision, visual consistency, and brand standards in AI-generated outputs received from the client.
The AI-generated visuals often captured the garment's overall look but missed critical details, such as neckline shape, sleeve length, buttons, pleats, logos, and fabric patterns. These gaps made the images unsuitable for direct use without precise manual correction.
Clothing edges, fabric fall, skin rendering, hands, and other non-target areas could appear distorted or artificially blended. The challenge was to refine these areas without making the final visual look disconnected from the original model image.
Skin tone shifts, lighting variations, and subtle changes in model proportions between images are common in AI outputs. Ensuring uniform skin tone, hair color, body proportions, and height across a diverse model lineup—spanning different ethnicities, ages, and body types—required constant cross-referencing. AI introduced subtle variations between images that, left uncorrected, would make a product catalog appear unprofessional.
Retouching demand could spike to 100–300 images per day, while instructions still varied by SKU and garment type. The challenge was maintaining accuracy and output consistency even during high-volume periods.
To support the client’s workflow, we deployed a dedicated team of five retouchers and QC experts to manage the final image correction process. Their role was to fix AI-generated distortions, restore product accuracy, and ensure every image met the required quality standards.
Each SKU was mapped to its retouching instructions before editing began, giving editors a clear reference point for every decision. This reduced cross-SKU errors and helped maintain control across high-volume batches.
Each AI-generated image was reviewed alongside the original product photo. The focus at this stage was to identify and correct every visible deviation so the final image matched the source product in both detail and appearance.
We focused on correcting the visible compositing marks left behind by AI garment placement. Our editors manually refined clothing boundaries to ensure the garment followed natural fabric flow, blended cleanly with the model’s body, and looked visually consistent with a professionally shot fashion image.
AI-generated images within the same batch often varied in lighting, shadow direction, color temperature, and exposure. To keep the final catalog visually consistent, our team standardized these elements across the full image set, so every output followed the same visual style.
The client’s AI could generate the initial on-model image, but key accessories and detail work still needed manual refinement. To complete each output, our team added and adjusted accessories, checked consistency across the image set, and enhanced visible details that affected the garment's final look.
Because the image sets included models across different ethnicities, age groups, and body types, even minor AI-generated inconsistencies could make the catalog look uneven at the batch level. To maintain a consistent presentation, our team standardized the model's appearance across all image sets.
Once approved, each image was prepared according to the client’s required output specifications so it could move directly into upload and catalog workflows. This final stage ensured that every file was correctly formatted, labeled, and organized for final delivery.
The end client (fashion brands) uploads a flat-lay or packshot of their products to the client’s platform.
The client’s proprietary virtual try-on AI processes the product image and generates an on-model visual, placing the garment on an AI-generated model.
The AI-generated image is sent to our team for precision retouching, covering product accuracy, accessory integration & model consistency.
Our team delivers the corrected, brand-ready assets back to the client after passing all quality control checkpoints in batches.
The client shares the finished, publication-ready images with the end client for use across eCommerce storefronts, catalogs, and marketing channels.
99% first-pass approval rate
across all retouched image batches, with fewer than 1% of deliverables requiring revision after final quality control sign-off.
40% reduction in per-image turnaround time
achieved within the first 60 days, driven by SKU-level briefing instructions and distributed quality checkpoints that reduced rework and editorial decision time.
100% product identity accuracy
maintained across all delivered assets—zero instances of incorrect color, missing construction details, or unresolved logo distortion reaching the client.
300+ images processed per day
at peak volume, without extending agreed turnaround windows or compromising output quality.
80% reduction in post-delivery revision requests
compared to the client's prior retouching process, reflecting the effectiveness of the pre-production briefing and multi-stage QC framework.
25,000+ images delivered
across multiple apparel and accessory categories within the first six months of the engagement, spanning outerwear, topwear, bottomwear, footwear, and jewelry.
Leverage our expertise to correct AI-generated distortions, restore product accuracy, and deliver consistent fashion visuals at scale. To get a free sample or share your project requirements, write to us at info@suntecindia.com.