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$NTSK began as a CASB vendor, governing how employees use SaaS applications at the point of use. Years of that work gave it application-specific knowledge of user behavior, data movement, and risk inside cloud apps. That knowledge carries over to AI. Netskope inspects prompts, responses, and file transfers inline and in real time, and it can respond with something more precise than a block: preventing a risky copy-and-paste, stepping up authentication for a sensitive interaction, or coaching the user as they work. The part that matters more comes after the prompt. AI adds autonomy and chaining, so a single human interaction can trigger many machine-executed actions across tools, data stores, and services, often outside one user session. If data is over-permissioned and tools are loosely scoped, an agent can stay inside its allowed permissions and still cause harm faster than a person can intervene. The context Netskope gathers at the interaction can be carried forward to constrain that downstream execution: who the user is, what data is involved, which action was taken, and how risky it looks. So Netskope's edge is that it already knows the user, the data and the action at the moment of the prompt, and it can use that context to limit what an agent does next. It is now building the agent side directly. Its Agentic Broker rates agent actions by risk before they run, and its AI posture management for agents built on AWS, Azure and GCP is still in preview. That is the part to watch.

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Research Roundup Vol. LV

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SLGN · long

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