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.
About graphrag
microsoft/graphrag
A modular graph-based Retrieval-Augmented Generation (RAG) system
Extracts knowledge graphs from unstructured text using LLMs, then uses those graph structures to improve retrieval and reasoning for private data. Implements a data indexing pipeline that transforms narrative documents into entity-relationship graphs, enabling more contextual and discovery-oriented query responses compared to standard vector retrieval. Supports prompt tuning workflows and integrates with major LLM providers through a configuration-driven architecture.
About VeritasGraph
bibinprathap/VeritasGraph
VeritasGraph: Enterprise-Grade Graph RAG for Secure, On-Premise AI with Verifiable Attribution
Combines hierarchical tree-based navigation with semantic knowledge graph reasoning to enable multi-hop retrieval and 100% verifiable attribution. Supports multiple deployment modes—lite with cloud APIs (OpenAI/Anthropic), local with Ollama (~8GB RAM), or full production with Neo4j—while including built-in vision RAG for extracting structured data from charts and tables. Integrates with optional UI (Gradio), Microsoft GraphRAG, and ingestion tools (YouTube/web articles).
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