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Architecture Note

Onshore Knowledge Vaults and RAG for a Sovereign AI Factory

Architecture guide for implementing Retrieval-Augmented Generation (RAG) with onshore, tenant-isolated knowledge vaults for regulated workloads in Australia's Sovereign AI Factory.

By SCX.ai Architecture Team7 min read

Retrieval‑Augmented Generation (RAG) is most effective when built on an onshore, tenant‑isolated knowledge vault. This ensures Australian data stays in Australia while delivering accurate, up‑to‑date answers for regulated workloads.

Design Considerations

  • Tenant‑scoped vector stores with encryption at rest and in transit
  • Document governance: classification, PII scrubbing, retention policies
  • Freshness pipelines for regulatory updates and internal knowledge

Query Path

  1. Classify input and apply policy tags
  2. Retrieve onshore passages; attach provenance and confidence
  3. Generate with Australian locale and compliance context

Key Takeaways

  • RAG quality depends on disciplined ingestion and governance
  • Onshore vaults preserve sovereignty and reduce compliance risk
  • Provenance and audit trails are non‑negotiable for enterprise outputs

Related Topics

RAGretrieval augmented generationknowledge vaultvector storedata sovereigntytenant isolationdocument governanceAustralian AIenterprise RAGonshore AI
Onshore Knowledge Vaults and RAG for a Sovereign AI Factory