Graph DBNLPEntity ExtractionNeo4j
Knowledge Graph Builder for Companies
Automated construction of organizational knowledge graphs from internal documents, databases, and APIs — enabling semantic search and relationship discovery.
This project is currently in active development.
The Problem
Enterprise knowledge is siloed across documents, databases, and APIs with no semantic connections between them. Teams cannot discover relationships between entities, decisions, or concepts without manual effort.
The Solution
An automated NLP pipeline that extracts entities and relationships from heterogeneous sources and builds a queryable knowledge graph in Neo4j — enabling semantic search and cross-domain relationship discovery at organizational scale.
Architecture
01Multi-source ingestion from documents, databases, and APIs
02Named entity recognition and relation extraction
03Automated ontology construction and refinement
04Graph storage and indexing in Neo4j
05Semantic query interface with graph traversal
Results & Outcomes
Unified semantic layer over previously disconnected enterprise data
Semantic search across the full organizational knowledge base
Automated entity resolution across multiple heterogeneous sources
Graph queries replacing complex multi-table SQL joins