From the practice of Masferre and Red Dragonfly Shoes, we can see the differentiated value of AI in different scenarios [Dajing AI Case Study]

At present, AI is no longer limited to the role of an efficiency tool, but has transformed into a core engine driving corporate growth. This article combines two benchmark cases, Masferre and Red Dragonfly Shoes, to deeply analyze how AI technology can create differentiated value in different scenarios, and provide a practical path for reference for corporate AI implementation and digital transformation.

Case 1: Three major evolutions of the intelligent agent "Phil"

As a leading company in China's high-end fashion apparel field, Masferre launched the transformation to centralized private domain operations in 2024, creating the intelligent entity "Phil" through AI Agent technology to accurately solve the problems of improving service efficiency and customer value.

10 groups of response strategies to achieve 7×24h seamless service

Based on LinkAI workflow capabilities, "Phil" sets 10 groups of personalized time periods to match modes such as manual takeover, manual supervision, and AI automation. For example, it automatically responds to routine inquiries during non-working hours at night, and reminds operations to handle replacement needs that require manual intervention the next day, achieving zero service interruption.

Expert knowledge base: 200+ scene knowledge for accurate responses

Relying on LinkAI RAG capabilities, Masferre has built a corporate knowledge base covering more than 200 scenarios including brand introduction, product consultation, after-sales processing, etc. "Phil" can accurately identify customer intentions, such as quickly answering questions such as logistics inquiries and return and exchange rules. Questions beyond knowledge are politely directed to the corresponding channels to ensure professional service.

Multimodal interaction + AI tagging to achieve accurate matching of people and goods

Through the Prompt project, "Phil" can recommend matching items based on the product pictures uploaded by customers, their dressing needs (such as scenes, color preferences, etc.), and the product library information, and directly push the link to the mall mini program. At the same time, AI automatically labels customers based on the conversation history (such as "new product followers" and "high-frequency repeat purchasers"), and pushes personalized information in a targeted manner based on festival activities, new product launches and other nodes, increasing the private domain repurchase rate by nearly 60%.

Case Summary

We have shifted from "extensive traffic operation" to "fine management of customer assets", freeing up human energy through AI, upgrading private domain operations, and focusing on in-depth services for VIP customers. We have built a dual-wheel drive system of "AI wide-area coverage + in-depth human services", taking into account both service efficiency and warmth, and maintaining high customer satisfaction in the industry.

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Case 2: Four breakthroughs of Red Dragonfly Shoes AI design platform

Faced with the dilemma of the shoemaking industry being "big but not strong", Red Dragonfly and Huilima jointly created the "VALI Shoe AI Design Platform" to use AI technology to solve pain points such as inefficient design and insufficient coordination in the industrial chain.

Building the industry's first footwear knowledge graph

Integrate data such as shoe design, raw materials, and processes to build a standardized industry knowledge system, break the unstructured knowledge barriers of traditional experience-based industries, and realize parametric storage and reuse of design elements.

AI generated 2.6 million design drafts, and the proportion of S/A models increased by 5%

Based on deep learning algorithms (such as CNN and diffusion models), the platform supports 9 major functions such as color matching, style fusion, and base design. The efficiency of designers' drawings has increased by more than 100 times, and the number of effective designs has increased by 1.5 times. Taking Red Dragonfly as an example, the proportion of best-selling models (S/A models) among 100 shoe models increased by 5%, and the sales of personalized customization increased by 30%.

Open up the digital material library of 1,000+ suppliers

The platform connects with more than 1,000 raw material suppliers, and designers can directly call up the real material library in the design draft, achieving seamless connection of "design-material selection-production". The material waste rate in the R&D stage is reduced by 20%, and the physical proofing is reduced by 60%.

Consumers directly participate in design and customization

Introducing consumer DIY design functions, supporting personalized customization such as parent-child models and couple models, narrowing the distance between users and brands, and promoting the transformation of "manufacturing" to "smart manufacturing + customization".

Case Summary

Traditional manufacturing can achieve the reconstruction of the entire chain of "research-production-sales" through AI, improve product competitiveness from the design end, and reduce inventory and costs. A successful industry platform needs to integrate the "technology (AI big model) + data (industry knowledge base) + ecology (supply chain collaboration)" triangle, such as the collaborative system formed by Huilima's "Good Goods" and "Good Purchasing" modules.