semantica vs utopia
Graph-native context infrastructure for accountable AI: ingest enterprise data, extract a knowledge/context graph (RDF + LPG), run graph analytics and causal reasoning with decision provenance. — versus — DeepLethe's open 'enterprise world model': one Rust binary plus Postgres running a bitemporal knowledge graph with ontology packs, cited hybrid search, an agent harness and MCP. Air-gap ready.
Both build a governed knowledge graph from enterprise data as the context layer agents reason over. Semantica is graph-native infrastructure you assemble; Utopia is a complete application — console, graph browser, ontology workbench — in one binary.
| semantica | utopia | |
|---|---|---|
| Stars | 12k | 4.5k |
| Forks | 1.3k | 422 |
| Language | Python | Rust |
| License | MIT | Apache-2.0 |
| Last activity | 2 days ago | today |
| Topics | knowledge-graphs | knowledge-graphs, rag |
| Curated connections | 8 | 5 |
semantica — the curator's take
The accountability angle is the real differentiator — decision provenance and deterministic reasoning aimed at regulated domains, where 'the agent decided' isn't an acceptable audit trail. W3C-standards + both RDF and LPG is rare breadth. When NOT: the README's marketing density ('open-source Palantir') outruns its documentation depth — prototype the core path before betting a compliance program on it; ★2.3k and the platform surface is huge for the team size.
utopia — the curator's take
For a company that wants a governed knowledge base its agents can trust, on its own hardware: ingest PDFs/Office/Markdown and sync sources (GitHub, Jira, Notion, S3), extraction follows an ontology you pick at creation (schema.org, W3C Org, PROV-O, FOAF, IOF ship in the binary), facts are bitemporal so you can ask what was known as of a date, and a built-in agent walks the graph with the same read-only tools exposed over MCP. Tantivy full-text is embedded, vectors go in pgvector, the job queue is a table — nothing else to run. NOT a memory layer for an agent app (it is a product, not a library) and not for a single person's notes: the ontology and audit machinery only pay off when several people and agents share the knowledge.