Complete architectural guide to deploying zero-leakage enterprise search and question-answering inside a private AWS/GCP VPC.
"Sending corporate contracts, internal medical charts, or financial ledgers to public AI APIs creates profound data leakage liabilities. Learn how we engineer air-gapped RAG pipelines inside private customer VPCs."
The Necessity of Sovereign AI
When enterprise clients approach **i26 Systems**, their primary hesitation around GenAI is security and compliance. Financial and healthcare regulations prohibit data egress outside controlled sovereign perimeters.
By orchestrating **Llama 3 70B** and **pgvector** inside private subnets with no internet gateways, enterprises unlock state-of-the-art AI capabilities while guaranteeing 100% data custody.
The Sovereign Architecture Stack
1. **Inference Server**: vLLM deployed on an Amazon EC2 `g5.12xlarge` or `p4de.24xlarge` cluster with continuous batching and PagedAttention.
2. **Embedding Generation**: Local BAAI/bge-large-en-v1.5 model serving embeddings in 12ms per chunk.
3. **Storage & Retrieval**: PostgreSQL 16 with `pgvector` utilizing HNSW (Hierarchical Navigable Small World) index graphs for sub-25ms approximate nearest neighbor queries.
4. **Guardrails & Verification**: All model outputs are cited against specific document chunk hashes with deterministic attribution.