Synapse

PythonNeo4jLangChainRAGKnowledge Graphs

Corporate Manager Intelligence. Optimizes management of complex corporate hierarchies. Uses Knowledge Graphs to map parent-child company relationships for clearer entity resolution and risk assessment.

View Source Code

Project Demo

Project Overview

Designed for enterprises managing extensive subsidiary networks. This project leverages Knowledge Graphs to map and analyze complex ownership structures that traditional relational databases struggle to handle efficiently.

Business Value

•Entity Resolution: Automatically links child companies to their ultimate identifiers.

•Complex Querying: Answers questions like "What is the total revenue exposure of Company X through all its 3rd-tier subsidiaries?"

•Multi-Hop Reasoning: Traverses deep hierarchy trees to find hidden connections.

Implementations

•Graph RAG: Uses Neo4j to store and retrieve structured knowledge, enabling "multi-hop" reasoning.

•Hybrid Search: Combines vector embeddings from ChromaDB with graph traversal queries for superior context retrieval.