Enterprise GraphRAG System
Architected a GraphRAG solution using LangGraph and Neo4j for an industrial automation group in the packaging sector.
Architected and implemented a GraphRAG (Graph-based Retrieval-Augmented Generation) system for an industrial automation client in the packaging sector. The system integrates a knowledge graph (Neo4j) with LLM-powered retrieval to answer complex technical queries across thousands of process and maintenance documents. Key responsibilities included designing the data flow from raw documents to the graph, implementing embedding and indexing pipelines, and orchestrating retrieval and generation with LangGraph. The architecture ensures that answers are grounded in the graph and that sources can be traced back for compliance and debugging.
System design
Data flow: ingestion (documents → graph) and query (user question → retrieval → LLM → answer).
Reduced manual search time from hours to seconds