Whitepaper

Technical Product Overview

Caber's AI Data Control Architecture and Product Overview

This technical overview defines Caber's AI Data Control architecture and the structural requirements necessary to govern data contribution at inference time. It explains why control signals such as policy, relevance, semantic meaning, business context, and usage-derived feedback must be evaluated together, and why specific integration patterns and latency constraints are unavoidable for closed-loop control of data fragments in enterprise AI systems.

Key Insights:

  • Global AI regulation landscape and key requirements
  • Data minimization strategies for AI training and inference
  • Automated compliance monitoring for AI systems
  • Right to explanation: Making AI decisions auditable
  • Building regulatory-ready AI governance frameworks
Technical Product Overview
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