Diagram gallery

Fig 1 · Reference architecture: system context.

Fig 2 · Reference architecture: the data flow, step by step.

Fig 3 · Reference architecture: integration flow.

Fig 4 · Platform architecture. One governed path from your surfaces to any model.

Fig 5 · Model egress: every request clears two gates.

Fig 6 · How a prompt traverses the Semantic Security Engine. One composed decision, landing before the model.

Fig 7 · The Security Context Graph: every decision becomes context for the next.

Fig 8 · Where the engine's models run, and where your prompts go.

Fig 9 · Local processing and residency, by deployment model and region.

Fig 10 · Who can see your data: the boundary by deployment option.

Fig 11 · The product map: where things run, what you add.

Fig 12 · Two products, and the ways your people access Secure Enterprise AI Workspace.

Fig 14 · Deployment paths over time: Secure Enterprise AI Workspace, the Endpoint Security, or both.

Fig 14a · Deployment path: Secure Enterprise AI Workspace.

Fig 14b · Deployment path: the Endpoint Security.

Fig 14c · Deployment path: both together.

Fig 15 · The posture ladder: enforcement climbs as the rollout widens.

Fig 16 · Enforcement at the endpoint: the decision lands before the model API.

Fig 17 · Alongside your stack: what flows in, what flows out.

Fig 18 · SIEM integration. Decision events and sealed evidence into your SIEM.

Fig 19 · Enterprise knowledge flow. Source permissions inherited and enforced at index and retrieval.

Fig 20 · Microsoft 365 and Copilot integration.