Industry background and pain points
Style decision-making relies on manual experience
Traditional ODM relies on experience in product selection, pattern design, color matching, and lacks data support, resulting in low hit rates and high trial and error costs for new products
Trend capture lag
The response to hot trends in emerging channels such as social media and e-commerce platforms is slow, making it difficult to quickly match personalized consumer needs
Serious homogenization competition
Plagiarism is frequent in the mid to low end market, and there is a lack of design innovation, leading to price competition and reduced profits
Solution
Trend Insight
Based on AI analysis of global fashion trends, generate seasonal/category trend reports to assist enterprises in accurately grasping market demand
AI Selection
By using the "Zhiyi" SaaS tool, the entire process from competitor analysis, explosive product mining to style recommendation can be digitized, increasing the style acceptance rate to 70% and doubling the explosive product rate
AIGC Auxiliary Design
Launching FD+tool to automatically generate design drafts and provide multi-dimensional optimization suggestions, increasing designer efficiency by three times and reducing sample clothing costs by 95%
Customer Cases
UR Group
Through the AI selection system of Zhiyi Technology, the number of new styles in the quarter increased by 50%, and the explosive rate increased to 45%
The Taiping Bird
After connecting to the flexible supply chain platform, the order delivery cycle has been shortened from 45 days to 21 days, and the emergency order response capability has been improved by 80%
Masfield
Masfel: By using AIGC design tools, the cost of single product commercial auction has been reduced by 90%, and the speed of new product launch has been increased by three times
