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RAGFreeOpen Source
SEMANTICA
Graph-native context layer for accountable AI systems
MIT
ABOUT
Vector RAG returns similar chunks with no structure, relationships, or audit trail, so regulated teams cannot answer why an agent decided something. Semantica builds a context graph with OWL/SHACL ontologies, Datalog reasoning, and PROV-O provenance so retrieval, policy, and decisions are inspectable.
INSTALL
pip install semanticaINTEGRATION GUIDE
1. Build a governed knowledge graph from Databricks, Snowflake, or SAP tables
2. Trace an agent decision with W3C PROV-O provenance for a compliance review
3. Run SPARQL or Datalog reasoning over enterprise entities instead of embedding search
4. Give CrewAI or LangChain agents a structured context graph instead of a flat vector index
TAGS
pythonknowledge-graphragprovenanceontologyreasoningenterprise