How is sovereign AI different from data sovereignty?
Data sovereignty is about where data lives and moves. Sovereign AI adds the models, the AI lifecycle and the systems that govern them, so the controls themselves stay inside the boundary. BigID covers both on one platform, which is why this page brings them together.
Which capabilities does the air-gapped deployment include?
It runs the exact same software, AI included. Discovery, classification, remediation, AI governance, APIs, reporting and MCP-based agent workflows are equivalent in every deployment mode. The AI runs on the model you install inside the network, so nothing depends on a hosted API.
We are moving to a sovereign cloud. What does BigID add?
It shows what the sovereign cloud holds and what leaves it. A sovereign cloud decides where infrastructure runs. BigID finds the regulated data inside it, maps the flows to other regions and vendors, shows who and what can reach it, and deploys inside the same boundary, with the options laid out in secure AI-first architecture.
What is data sovereignty?
Data sovereignty means data stays subject to the laws of the place it is collected or stored. In practice that means knowing where regulated data lives, where it travels, and who can reach it. BigID builds that picture from discovery, then applies localization policy and keeps the evidence, starting from data discovery and classification and privacy and compliance.
Which regulations drive sovereignty requirements?
GDPR transfer rules, the EU Data Act, DORA, NIS2, and the EU AI Act lead in Europe, alongside national laws such as India's DPDP, China's PIPL, and Brazil's LGPD, and the DOJ rule implementing EO 14117 in the United States. BigID supplies the findings and evidence each one asks for, and public sector sovereignty levels and CISA's CI Fortify add requirements for where the platform itself runs.
How does BigID keep AI inside the boundary?
It shows where each model runs and what data it reaches, then governs both locally. BigID inventories models, agents, and AI pipelines with their training and retrieval data, tracks where prompts and outputs go, keeps agents to data inside the boundary through the identities they run under, and runs its own AI on the approved model you choose, including with no outbound connection. AI governance and secure AI-first architecture cover the detail.