Auto Ontology de NVIDIA garantiza que los agentes de IA generen SQL preciso al fundamentarlos en definiciones de negocio certificadas, evitando errores costosos en el análisis de datos empresariales.
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NVIDIA has released Auto Ontology, an open library under the Apache 2.0 license. NVIDIA Auto Ontology is a semantic layer framework that builds a context layer from enterprise metadata. Agents use that layer to write SQL against certified business definitions. The repository states the problem plainly: a fast revenue answer is worthless if the number is wrong. TL;DR Library: Default LLM is nvidia/nemotron-3-nano-30b-a3b, with Nemotron embedding and reranking models. Runs on: Docker Compose for a local stack, or Kubernetes via Helm. Inference uses hosted NVIDIA NIM endpoints or self-hosted NIMs. Performance: Strong engineering, thin public evidence. Best: Ontology creation time cut by 90% in NVIDIA testing (self-reported). Worst: 0 published text-to-SQL accuracy scores. The eval repo ships a harness, not results. Bottom line: An open, MCP-ready context layer that any agent harness can query. But you must run the benchmarks yourself to trust it. What is NVIDIA Auto Ontology? It is a context layer that sits between an agent and the data warehouse. It tells the agent where data lives and what fields mean. It also says whether to use a field, how to use it, and where it came from. Here are the five jobs: Discover: generate ontologies from metadata and connect existing semantic models. Ground: give agents trusted meaning for metrics, entities and relationships. Validate: check generated queries against certified definitions and lineage. Expose: serve context through MCP, CLI and API. Learn: fold certified corrections back into the ontology. NVIDIA’s developer page frames the output as a starting ontology. Business experts still test, refine and certify it. How does Auto Ontology work? The stack has 4 core services. A Next.js 16 frontend handles the web UI and authentication on port 3000. A FastAPI backend with LangChain runs chat, NL-to-SQL and catalog APIs on port 3001. An ingestion worker writes embeddings on port 3002. Postgres with pgvector store
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