Semantica

Semantica is an open-source enterprise-grade knowledge graph tool designed for AI agents, targeting companies rather than individuals, and transforming enterprise data into structured knowledge graphs.

Semantica's core module Context Graph traces information sources and usage paths by studying node relationships, while Decision Intelligence retains candidate solutions, decision rationale, and final conclusions.

Semantica can export decision chains as audit archives in W3C PROV-O format.

Semantica has dual-temporal awareness capabilities, capable of recording both the time an event occurs and the time an Agent perceives it.

Semantica automatically organizes scattered data into a visual relationship network, assists with reasoning, preserves decision records, and enables tracing back from conclusions to original sources.

Semantica constructs two graphs as reasoning infrastructure: a Context Graph and a Knowledge Graph.

Semantica is an open-source reasoning engine that pursues making AI decisions traceable, auditable, and explainable, rather than pursuing higher accuracy.

Semantica supports bitemporal facts, simultaneously tracking when a fact is true in the real world and when it is recorded in the system, enabling point-in-time graph snapshot playback of history.

Semantica is an open-source infrastructure designed to transform opaque, chaotic AI decision-making processes into clear, traceable, and auditable records.

Semantica's process of transforming raw data into an accountable graph is a deterministic four-step pipeline—ingestion, extraction, conflict detection, and construction—running entirely independently of LLMs.

Semantica is fully open-source and supports polyglot storage, compatible with Blazegraph (RDF triple store), Neo4j, AWS Neptune (labeled property graph), as well as FAISS and pgvector (vector stores).

Semantica can connect directly to data sources such as Databricks Unity Catalog, Snowflake, and SAP OData, and is compatible with agent frameworks such as LangChain, Agno, and CrewAI, with no need to export data to third-party SaaS.

In the Semantica 0.6.8 update, candidate generation and caching mechanisms were optimized, achieving a 6,000x improvement in node search speed on a production-grade graph with 118,000 nodes compared to the baseline, and a 10x improvement in embedding cache throughput.

Semantica supports automatic ontology generation and also supports SHACL for checking whether fields, types, and relationships conform to constraints using predefined shapes.

Semantica distinguishes between when a fact holds true in reality and when the system becomes aware of and stores it, and uses Allen's interval algebra to express temporal relationships such as before, overlaps, and contains.

Semantica can discover duplicate entities using string similarity, semantic similarity, and merge strategies, and can detect and flag contradictory facts.

Ontologies automatically generated by Semantica are still only drafts; Chinese-language and multimodal scenarios may require additional adaptation, and large-scale deployment brings storage and operational costs.

Semantica is not a chatbot, nor merely a RAG tool that chunks documents into small pieces; instead, it organizes content from files, databases, and interfaces into machine-queryable facts and relationships, recording sources, validity periods, and decision participation.

Semantica connects the ontology to data ingestion, entity recognition, querying, reasoning, and validation, making it a business rules layer that agents pass through with every operation.

Semantica's provenance records can use SHA-256 digital fingerprints to check whether records have been tampered with.