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SecuritySeptember 20, 20245 min read

Data Sovereignty in the AI Age: Why It Matters More Than Ever

As AI systems process ever more sensitive data, organizations must ensure their content stays within their control. Here's how Straker approaches data sovereignty.

James Wu

Chief Information Security Officer

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The rise of cloud-based AI has created a data sovereignty crisis. Organizations are sending their most sensitive content—financial reports, legal documents, customer data—to third-party AI systems with little visibility into how that data is stored, processed, or potentially used for training.

The Hidden Risks

When you use a general-purpose AI service, your data may be:

  • Stored indefinitely: Even after your session ends
  • Used for training: Improving models that competitors also use
  • Processed in unknown locations: Potentially violating GDPR, CCPA, or industry regulations

Straker's Approach

We built our infrastructure with data sovereignty as a core principle:

  • Private Model Training: Your Tiri model is trained exclusively on your data and used only by you
  • Regional Processing: Choose where your data is processed—US, EU, APAC, or on-premise
  • Zero Retention: Content is processed and immediately purged—never stored, never used for training
  • SOC2 & ISO 27001: Enterprise-grade security certifications

Compliance by Design

For regulated industries—finance, healthcare, legal—data sovereignty isn't optional. Our infrastructure is designed to meet the strictest compliance requirements while still delivering the speed and scale benefits of AI.

SecurityData SovereigntyCompliance

James Wu

Chief Information Security Officer

Contributing to Straker.ai's mission to bridge the gap between AI efficiency and human trust.

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