New Retail Giant Reduces Costs 45% with TiDB’s GraphRAG System

This case study focuses on a leading player in the New Retail industry, a company known for its innovative approach to food service and customer experience. With a vast network of outlets and a diverse workforce, the company faced the challenge of managing and accessing a rapidly growing volume of internal knowledge. This included technical documentation, operational manuals, recipes, and other critical information spread across various sources, leading to inefficiencies and hindering operational agility.

The Challenge: Streamlining Knowledge Management While Enhancing Operational Efficiency

Despite having a robust technical infrastructure, the company encountered significant challenges in knowledge management across two critical areas:

1. IT Operations: The company’s IT team was large but struggled to efficiently access and integrate essential technical documentation for system maintenance and troubleshooting. Engineers found themselves spending excessive time searching through multiple documentation sources to find solutions for issues that arose during operations. As a result, downtime increased, affecting overall productivity.
2. Restaurant Operations: Store managers and staff required quick and accurate access to operational documents including standard procedures, recipes, and safety protocols. Given the diverse backgrounds of employees, from seasoned managers to new hires, there was an urgent need for a simple yet powerful solution that could provide immediate access to relevant information without overwhelming users with complexity.

The urgency of these scenarios prompted the company to seek out a more effective knowledge management solution that would streamline access to crucial information while enhancing operational efficiency.

The Solution: Enhanced Knowledge Management with TiDB’s GraphRAG System

To address these challenges, the company implemented TiDB’s GraphRAG solution—a cutting-edge knowledge graph-based RAG (Retrieval Augmented Generation) system powered by TiDB Vector Search. This solution effectively bridges the gap between disparate data sources by enabling contextual retrieval of information tailored specifically for both IT operations and restaurant management scenarios.

By utilizing GraphRAG technology, the implementation provides an intelligent knowledge base that allows engineers to quickly find relevant technical documentation while also empowering store employees to access necessary operational guidelines seamlessly.

Tech Stack

The solution integrates several advanced technologies:

• TiDB Cloud Serverless: Serves as the primary database platform providing scalability.
• TiDB Vector Search: Enhances semantic understanding for precise document retrieval.
• AutoFlow: Implements GraphRAG capabilities for conversational interactions.
• Embedding with Jina.ai: Facilitates efficient vectorization of documents.
• LLM Integration with AWS Bedrock/OpenAI GPT Models: Powers natural language processing capabilities for user queries.

How It Works

The GraphRAG solution operates through a streamlined process designed to meet both IT and restaurant operation needs:

1. Knowledge Graph Extraction: The system extracts knowledge graphs from existing documents—such as technical manuals and operational procedures—and creates structured mappings of entities and relationships. By storing this structured information in TiDB along with vector embeddings, it ensures efficient retrieval.
2. Query Processing: When users input queries—be it IT engineers seeking troubleshooting steps or restaurant staff looking for recipe guidelines—the system employs intent detection algorithms to understand their requests accurately. It then performs multi-path retrieval using both vector search capabilities for related content and graph search techniques for contextual relevance.
3. Response Generation: After retrieving relevant information, the system synthesizes responses tailored to each user’s context. For instance, if an engineer asks about backup procedures during peak hours, the system will provide not only direct answers but also related resources such as dependencies or previous incident reports.

Solution Demo

To see this in action, visit TiDB.AI. The platform serves as an intelligent documentation assistant built using GraphRAG technology combined with TiDB Vector Search capabilities. Users can interactively ask questions like “What is the process for handling equipment failures?” or “How do I update our inventory records?” with confidence that they will receive accurate and contextual answers drawn from a comprehensive knowledge base.

Building your own version with the open source project AutoFlow!

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The Results: Fast Issue Resolution and Enhanced Compliance

The implementation of TiDB’s GraphRAG solution yielded significant improvements directly tied to the initial scenarios.

For IT operations, engineers reported a remarkable reduction in time spent searching for documentation— now down from 30 minutes per query to just seconds—allowing them to resolve issues promptly without causing delays in system performance. The accuracy of retrieved information improved by 10%, which minimized miscommunication among teams when addressing technical problems.

In terms of restaurant operations, store managers now have rapid access to essential documents such as standard operating procedures or safety protocols at their fingertips via mobile devices or desktop interfaces. This ease of access has not only enhanced compliance but also empowered employees by reducing training times by approximately 40%.

Overall, the initiative led to:

• A 70% decrease in support ticket resolution time due to faster access to necessary documentation.
• A 90% user adoption rate among both technical staff and restaurant employees highlighting its effectiveness across different roles.
• A 45% reduction in costs associated with maintaining multiple fragmented knowledge bases.

By implementing TiDB’s GraphRAG solution, the company has successfully streamlined its knowledge management processes while significantly boosting operational efficiency across its vast network of restaurants and IT operations.