Brand Specialized Agent System

A professional agent trained with specific knowledge bases and RAG technology, providing rapid Q&A services for luxury brand operations teams regarding project data, technical details, and release schedules

Client Valentino / GUCCI
Completion Date 2/25/2024
RAGKnowledge BaseIntelligent Q&ABrand OperationsLuxury Goods

Project Overview

Project Overview

The Brand Specialized Agent System is designed specifically for top luxury brands like Valentino and GUCCI. Using RAG (Retrieval-Augmented Generation) technology to build professional knowledge bases, it provides intelligent Q&A services for operations teams regarding project data, technical details, and release plans. The system deeply integrates brand historical project materials and accurately understands and answers complex business queries.

Core Features

  • Intelligent Knowledge Base: Integrates all brand project documents, technical specifications, and release plans
  • Natural Language Queries: Supports Chinese and English natural language questions
  • Context Understanding: Understands complex query contexts and provides precise answers
  • Multi-dimensional Retrieval: Quick retrieval by project, time, technical type, and other dimensions
  • Permission Management: Controls information access based on user roles
  • Learning Optimization: Continuously improves answer quality based on user feedback

Technical Architecture

Knowledge Processing:

  • Document parsing: Supports multiple formats including PDF, Word, Excel
  • Semantic segmentation: Intelligently segments documents while maintaining context integrity
  • Vector storage: Uses ChromaDB for efficient vector retrieval

RAG Engine:

  • LangChain framework for building retrieval-augmented generation pipeline
  • Hybrid retrieval: Combines keyword and semantic search
  • Answer generation: Generates accurate responses based on retrieved content

System Integration:

  • FastAPI provides high-performance API services
  • React frontend provides user-friendly interaction interface
  • Elasticsearch supports full-text search
  • PostgreSQL stores user interaction data

Professional Customization

Valentino Specialized Version:

  • Integrates brand historical product line data
  • Fashion week release schedule queries
  • Supplier and material technical specifications
  • Marketing campaign timelines

GUCCI Specialized Version:

  • Product series technical parameters
  • Retail strategies and channel information
  • Brand collaboration project archives
  • Designer creative concept records

Workflow Process

  1. Knowledge Base Construction: Import brand project documents and historical materials
  2. Data Preprocessing: Clean, segment, and vectorize processing
  3. Model Training: Fine-tune models based on brand-specific data
  4. Intelligent Q&A: Users ask questions, system retrieves and generates answers
  5. Feedback Optimization: Collect user feedback and continuously improve the system

Innovation Highlights

  1. Deep Brand Customization: Deeply customized for each brand’s characteristics and needs
  2. Multi-language Support: Supports queries in Chinese, English, French, Italian, and other languages
  3. Real-time Updates: New project information synchronized to knowledge base in real-time
  4. Intelligent Recommendations: Proactively recommends relevant information and similar projects
  5. Visual Display: Complex data presented intuitively in chart formats

Business Value

  • Efficiency Enhancement: Quick access to project information, reducing query time
  • Knowledge Management: Systematic organization and utilization of brand knowledge assets
  • Decision Support: Provides data support for business decisions
  • Team Collaboration: Promotes cross-departmental information sharing and collaboration
  • New Employee Training: Quickly understand brand history and project situations

Technologies

LangChainChromaDBOpenAIFastAPIReactTypeScriptPostgreSQLElasticsearch

项目信息

Client Valentino / GUCCI
Completion Date 2/25/2024
Category Intelligent Assistant

Challenge

Luxury brand project information is complex, and team members need quick access to project data, technical specifications, release timelines. Traditional query methods are inefficient

Solution

Built a brand-specialized agent based on RAG technology, integrating brand historical project data to provide natural language queries and precise answers

Results

500% improvement in information query efficiency
95% accuracy rate in Q&A responses
60% improvement in team collaboration efficiency
80% increase in project document utilization
50% reduction in new employee training cycle