[Customer Testimonial] Bringing Dormant Fashion Data to Life: Yakjin Trading Reinvents Its R&D with AI

In a fast-changing fashion industry, legacy design archives remain a company’s most valuable asset and a catalyst for future creation. Yet at most organizations, these assets sit idle inside ERP systems, email, and personal laptops. Yakjin Trading, a global apparel manufacturer, partnered with Superb AI to awaken this “dormant data” and turn it into a core competitive advantage.

Challenge – “Please find that style from back then”: A loop of recurring inefficiencies

Yakjin Trading’s sales and design teams are highly skilled, but outdated retrieval methods consistently slowed them down:

• Communication bottleneck: When sales requested a specific style by email, design had to stop work and hunt through countless folders—taking anywhere from minutes to over half a day—and productivity suffered on both sides.
• Search limitations: Finding buyer-requested styles each season via ERP systems was difficult. Text-based ERP search had clear limits, and searching by visual design attributes in images was impossible.
• Knowledge silos: A process reliant on individual memory and experience prevented systematic data use, leaving valuable design assets underutilized.

Solution – An “AI Style Library” where every design always stays connected

To address these challenges, Superb AI built an “AI-Powered Fashion Style Library" that not only consolidated scattered data but also infused it with intelligence.

1. Bringing data to life with AI auto-tagging: At the core was auto-tagging powered by generative AI (Amazon Bedrock Claude). The AI analyzed tens of thousands of apparel images, automatically extracting precise design attributes and generating tags. Yakjin Trading’s archives were transformed into high-quality, searchable data.
2. An effortless search experience for everyone: With the simple drag-and-drop of an inspiration image, designers could instantly find similar in-house styles. Additionally, natural language search—e.g., “sleeveless dress with a floral pattern”—became possible. Filters that combine brand, season, and AI tags enable precise data search.
3. A one-click workflow: ERP data synced automatically with the library to keep it always up to date, and users could instantly download style images, work orders, and pattern files as needed. The entire process of opening emails, attaching files, and waiting for replies disappeared.

Benefit – Free the hours, free the ideas

The AI Library drove outcomes beyond expectations at Yakjin Trading:

• Maximized R&D productivity: It eliminated wasted search time and created an environment where employees could focus on core creative work.
• Data-driven design innovation: By analyzing past successes and the usage frequency of specific design elements, the team could develop new styles based on data rather than intuition.
• Shift in collaboration culture: With sales and design viewing the same data in real time, unnecessary misunderstandings and delays disappeared, enabling more organic collaboration.

Scalability – Envisioning the future of Fashion AI

This project is a beginning, not an end. The accumulated, high-quality tag data lays the groundwork for AI models that can forecast global fashion trends and even generate new design proposals. With data at the center, Yakjin Trading is now equipped to lead the market.