Architecture Overview
Edge-first design with optional cloud analytics
System Architecture
┌─────────────────────────────────────────────────────────────┐ │ Edge Device │ │ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │ │ │ NVIDIA Jetson│ │ Local LLM │ │ RAG │ │ │ │ Orin Nano │ │ + Guardrails │ │ Over PDFs │ │ │ │ (Vision AI) │ │ │ │ │ │ │ └──────┬───────┘ └──────┬───────┘ └──────┬───────┘ │ │ │ │ │ │ │ └──────────────────┴──────────────────┘ │ │ │ │ │ ┌────────▼────────┐ │ │ │ Anonymization │ │ │ │ Layer │ │ │ └────────┬────────┘ │ └────────────────────────────┼──────────────────────────────────┘ │ Metrics Only ▼ ┌─────────────────┐ │ Cloud Dashboard │ │ (Optional) │ └─────────────────┘
Local LLM with RAG
View RepositorySource: local PDF - data_policy.pdf (page 3)
✓ All processing on-device
Edge Vision Metrics
View RepositoryDetected: 3 objects
Inference: 45ms
{ "count": 3, "avg_latency_ms": 45 }
✓ Raw images stay local
What You Can See
Edge Vision
NVIDIA Jetson Orin Nano with local inference for real-time computer vision applications
Local LLM Chat
On-device language models with guardrails and RAG over your PDFs - no data leaves your infrastructure
Cloud Analytics
Optional cloud dashboards with anonymized metrics only - raw data stays local
Why It Matters
Data Stays Local and Compliant
Meet GDPR, HIPAA, and national security requirements with on-premises processing
Proven Patterns
Battle-tested architectures for national and enterprise sovereignty requirements
Fast Paths to Scale
Move from pilot to production with confidence using proven deployment patterns
How It Works
1. Edge GPU Processing
Vision models run locally with TensorRT or ONNX optimization for real-time inference without cloud dependencies
2. Local LLM with Guardrails
Language models run on-device with policy enforcement and RAG capabilities over your documents
3. Anonymous Metrics Only
Optional cloud dashboards receive only aggregated, anonymized metrics - never raw data