Semantica is an open-source, self-hostable infrastructure platform designed to build graph-native systems for AI agents that operate in high-stakes, regulated environments. Positioned as "the Open Source Palantir for AI Agents," it provides deterministic reasoning, decision provenance, and full auditability without requiring LLMs for graph construction or reasoning. The platform addresses a critical gap in current AI deployments: most agents store embeddings rather than meaning, leaving decisions unexplainable and unauditable—a compliance exposure in regulated domains like finance, healthcare, and government where an AI decision must survive regulatory scrutiny months after it is made.
The core purpose of Semantica is to sit underneath existing LLM, vector store, and agent frameworks as a deterministic infrastructure layer that transforms fragmented raw data into structured, queryable context. Rather than replacing existing tools, it complements them by adding decision records, causal reasoning, provenance tracking, ontology governance, conflict detection, and audit trails on top of whatever stack an organization already uses. The platform is built for AI and ML platform teams shipping consequential decisions, data platform teams on Databricks or Snowflake who need governed knowledge graphs without exporting data to third-party SaaS, compliance and risk teams requiring auditable answers to "why did the AI do that?", and regulated enterprises that cannot deploy black boxes or send sensitive data elsewhere.
Semantica's architecture is modular and end-to-end, with each stage independently importable.
The platform introduces two key concepts: Context Graphs and Decision Intelligence. A Context Graph is a structured memory layer answering "what is connected, why, and how?" rather than "what is similar?" Every entity, relationship, decision, and fact is a queryable node with full provenance, and conflicts are detected rather than silently overwritten. Decision Intelligence treats every AI choice as a permanent, auditable, queryable record with a full lifecycle, exportable as W3C PROV-O for regulator submission. This directly addresses compliance requirements in regulated industries.
Semantica supports native connectors for Databricks with Unity Catalog and Delta Lake support, and Snowflake with warehouse introspection and multiple authentication methods, allowing tables already in lakehouses or warehouses to become graph nodes with provenance without additional export steps. Graph analytics capabilities include centrality measures, community detection, link prediction, and shortest-path queries.
The repository is written in Python and classified across multiple domains including agent memory, AI governance, context engineering, knowledge graphs, graph RAG, explainable AI, and semantic search. The project emphasizes open-source availability, self-hosting capability, auditability, zero vendor lock-in, and W3C standards compliance for interoperability. It includes comprehensive documentation, a visual knowledge explorer for graph and ontology inspection, integrations with major agent frameworks, and a full-featured CLI for command-line operations.
