graphrag and VeritasGraph

GraphRAG is a general-purpose modular framework for building graph-based RAG systems, while VeritasGraph is a specialized enterprise implementation built on top of graph RAG principles with added emphasis on security, on-premise deployment, and verifiable attribution—making them complements rather than competitors.

graphrag
73
Verified
VeritasGraph
51
Established
Maintenance 17/25
Adoption 11/25
Maturity 25/25
Community 20/25
Maintenance 10/25
Adoption 10/25
Maturity 16/25
Community 15/25
Stars: 31,429
Forks: 3,319
Downloads:
Commits (30d): 8
Language: Python
License: MIT
Stars: 254
Forks: 25
Downloads:
Commits (30d): 0
Language: Python
License:
No risk flags
No License

About graphrag

microsoft/graphrag

A modular graph-based Retrieval-Augmented Generation (RAG) system

This system helps you make sense of large amounts of unstructured text data, like research papers or internal documents. It processes your text to identify key entities and relationships, outputting a structured knowledge graph that your AI can then use to answer complex questions or find insights more effectively. This is designed for researchers, analysts, or anyone who needs to extract precise information and reasoning from extensive narrative data using large language models.

knowledge-extraction research-analysis document-intelligence data-enrichment information-discovery

About VeritasGraph

bibinprathap/VeritasGraph

VeritasGraph: Enterprise-Grade Graph RAG for Secure, On-Premise AI with Verifiable Attribution

This tool helps professionals understand complex documents by turning them into interactive knowledge graphs. Instead of just searching for keywords, it maps how different pieces of information connect, allowing you to ask sophisticated questions and see the exact sources for every answer. It's designed for anyone who needs to quickly get verifiable, detailed insights from large amounts of information, like researchers, analysts, or legal teams.

knowledge-management research-analysis document-intelligence legal-tech enterprise-search

Scores updated daily from GitHub, PyPI, and npm data. How scores work