Developed a sovereign e-governance RAG infrastructure plan using LLaMA 3, QLoRA, and Milvus, solving strict data residency restrictions through secure air-gapped proxy server architectures.
Completely localized vector storage compliance
Cross-agency legal, farm, and civic workflow design
Balancing advanced e-governance RAG (Retrieval-Augmented Generation) lookup capabilities with strict national security regulations and citizen data residency laws.
Architected an air-gapped virtual private network structure and designed local sovereign LLM training pipelines with QLoRA and air-gapped vector databases.
Formulated isolation proxies that sanitise, parse, and scrub personally identifiable records before allowing indexing inside local vector databases.
Designed high-efficiency QLoRA training parameters for local LLaMA-3-70B models, optimizing them for regional dialects.
Configuring reverse proxy filters for sanitizing local vector lookups.
# Air-gapped secure vector sync proxy filter
server_name secure-ai.local;
location /RAG {
proxy_pass http://milvus_cluster;
# PII sanitation filter module active
}If something here looks like what you're facing, tell me about it. The first conversation is an architecture discussion, not a sales call.
