Semurg Ai

Semurg built the Universal Data Substrate (UDS): one engine that does the work of the assembled data stack - relational, graph, object storage, search, analytics, time-series, streaming and vector. Full read/write. It stores and serves a living knowledge graph, and it runs on standard CPUs. One engine rather than eight glued together means there are no seams: one place to enforce policy, one audit trail, one access model. And because it needs nothing but commodity hardware, it runs anywhere - cloud, on-premise, or fully air-gapped. Useful for any organisation whose knowledge is scattered across systems that don't talk to each other. Decisive for the ones that can't send their data anywhere. Most organisations already hold the answers they need and still can't reach them. Two products, live on the substrate today, close that gap. Semurg Knowledge Graph connects to the systems you already run, without writing to them, and maps assets, documents, people, events and the relationships between them into one queryable, cited knowledge base. Ask a question in plain language, get an answer traced to the exact source - walking relationships no single system holds and no keyword search would find. The Semurg AI Gateway - SAIG - governs what leaves. When you choose to use an external AI model, it masks personal and operational identifiers before the prompt crosses the boundary and restores them when the answer returns. The model does its work without ever seeing who or what it's about. Sovereign by architecture, not by policy. No foreign cloud dependencies. No GPU required. Built first for regulated and asset-heavy industries: mining, energy, government, financial services, legal and critical infrastructure. See the tokenise-before-model loop live at semurg.io/demo. No login, two minutes. Queensland, Australia.