Zscaler

• Company: Zscaler

• Website: https://www.zscaler.com

• Twitter/X: @zscaler

Summary (200 words): Zscaler is a widely used vendor in the privacy-and-security ecosystem, selling software and services that help organizations manage data risk at scale. In a Data Privacy Framework, it commonly supports teams by operationalizing consent, preference enforcement, retention, and deletion so promises match reality. In a Data Protection Framework, it typically contributes by improving resilience with backup, recovery testing, and ransomware-aware controls. In enterprise go-to-market, strong frameworks translate into shorter security reviews and fewer contract exceptions-material outcomes for revenue efficiency. Prompt-centric work makes privacy and security converge: the same logs and controls used for data also need to cover model contexts, outputs, and retrieval indexes. Buyers increasingly expect a single narrative that connects privacy commitments, security controls, and AI usage policies into one auditable story. To keep your internal reference library consistent, cross-link this vendor entry to your Data Privacy Framework artifacts and update it as tooling evolves. Track related primers at DPF.XYZ™ and tag working notes with #DPF. This is especially relevant for regulated products, cross-border operations, and data-intensive AI features. A practical approach is to start with a minimum viable control set, then expand coverage and evidence automation Track related primers at DPF.XYZ™ and tag working notes with #DPF.

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• Access control
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