What challenges did AtlasV face before AI implementation?

Traditional production requires models, photographers, studios, styling, and post-production resources. Manual workflows are slow and difficult to scale across multiple looks, scenes, and creative variations. Collart needed stronger AI image and video generation capabilities to make commercial visual production faster, more accessible, and easier to scale.

What was the impact of the AI solution?

Users can convert static product, model, outfit, and portrait images into AI-generated images and videos for social media, e-commerce, advertising, and personal branding. The solution reduces reliance on traditional shooting and post-production workflows. It enables faster multi-version creative generation and scalable production of visually rich content.

Source

AlibabaEvidence: Low40/100

AtlasV (Collart) Fashion/Portrait AI visual creation using Alibaba Wan 2.7 and Model Studio

Use case typeContent generationUpdated 1 day ago

AtlasV operates Collart, an AI visual creation platform for fashion, e-commerce, portrait, and social media content creation. It helps brands, merchants, and creators transform product images, model photos, selfies, and creative references into high-quality images and videos for marketing, social distribution, and personal branding. The company integrates Alibaba Cloud Wan 2.7 multimodal generation and Alibaba Cloud Model Studio into user-facing creation workflows so users can turn static assets into dynamic, commercially usable visual content faster.

Organization: AtlasV
Industry: Consumer & Food
Location: China
Published: July 2026

Reported outcomes

Strategic outcomes

Speed & agilityFaster commercial visual productionScale & capacityScalable multi-version creative generationCustomer experience & trustCommercially usable visual content for creators and brands

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: AtlasV, Collart
Provider: Alibaba
Maturity: Unknown
Linked source: Alibaba Cloud Customers

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 2 of 2

1Content generation
2Workflow automation

Traditional production requires models, photographers, studios, styling, and post-production resources.
Manual workflows are slow and difficult to scale across multiple looks, scenes, and creative variations.
Collart needed stronger AI image and video generation capabilities to make commercial visual production faster, more accessible, and easier to scale.

Collart integrates Alibaba Cloud Wan 2.7 capabilities into its user-facing AI creation workflows.
Users upload model images, clothing images, product photos, or complete outfits, then select a reference video to guide motion, camera rhythm, and visual atmosphere.
Alibaba Cloud Wan 2.7 image-to-video capabilities generate movements such as turning, walking, product showcasing, outfit transitions, and camera push-ins.
Alibaba Cloud Wan 2.7 image-to-image and image editing capabilities support portrait style transformation, background replacement, outfit changes, multi-image reference creation, and consistent visual series.
Wan 2.7 video editing, multi-shot generation, and audio-visual synchronization capabilities extend static images into complete short-form video assets.
Alibaba Cloud Model Studio is used to accelerate deployment and scaling of the models on a secure Alibaba Cloud platform.

Technologies

Alibaba Cloud Wan 2.7 Alibaba Cloud Model Studio Qwen

Users can convert static product, model, outfit, and portrait images into AI-generated images and videos for social media, e-commerce, advertising, and personal branding.
The solution reduces reliance on traditional shooting and post-production workflows.
It enables faster multi-version creative generation and scalable production of visually rich content.

Sources & evidence1

Evidence: Low40/100Evidence strength