Most organizations have an AI policy. Few can enforce it. Employees use public AI apps, SaaS applications embed AI features, developers rely on coding assistants, and agents call tools and take action. Static policies, committee reviews, and spreadsheet inventories cannot see or keep up with what happens inside these interactions.

AI governance only works when it can be enforced at the point of use and build. Aurascape closes that gap. It gives governance, security, and compliance teams a way to see AI use, classify risk, enforce approved tools, guide users, control agents, and preserve evidence, so policy turns into control.

Aurascape deploys as an additive control layer alongside your existing security stack. It also supports distributed governance: security owns global policy while legal, compliance, HR, data owners, and business units participate in decisions for their own domains without turning every request into a security ticket.

The solution brief covers shadow AI governance, AI Usage Control for sanctioned tools, sensitive data protection, Copilot and embedded AI readiness, coding assistant governance, and agentic AI and Model Context Protocol (MCP) governance. It also shows how Aurascape preserves audit-ready evidence for every AI interaction: who used AI, what tool, what data, what action, and what happened next.