Keep Your Data.
How To Build Private AI With NVIDIA Micro Computers.
Most people think AI means sending data to the cloud and getting smart answers back. For many real-world businesses, that is not always acceptable. Data is sensitive, internet links are unreliable, and nobody wants critical operations to depend on someone else's server. This white paper explains how to build local, fully offline AI services using NVIDIA Jetson micro computers.
Four reasons private AI on Jetson
beats cloud AI for real businesses
Privacy and Trust
Your video, audio, or transaction data never leaves the building. This keeps customers, regulators, and risk committees comfortable, especially in healthcare and finance.
Latency and Response
A LAN is faster than the internet. For safety alerts, process control, or on-the-spot recommendations, local processing beats remote processing every time.
Cost Control
Cloud GPU pricing grows silently. A one-time investment in a Jetson-based edge node is often cheaper over a 2-3 year period for steady workloads.
Resilience
If the internet fails, your AI does not. Production lines and clinics keep working because decisions are made right where the data is born.
The NVIDIA Jetson family,
and the cloud-free software stack
| Jetson Nano Dev Kit | $150 - $250 · Basic image classification, simple object detection (people present/absent) |
| Xavier NX Dev Kit | $350 - $600 · Real-time analytics, multiple cameras, speech models |
| Orin Nano / NX Dev Kit | $400 - $900 · On-device LLMs, multi-modal, compressed Llama models |
| JetPack SDK | NVIDIA SDK includes Ubuntu Linux, CUDA, cuDNN, TensorRT — an AI-ready OS with all drivers pre-installed |
| Docker + Python | Package apps for predictable deployment · Python 3, pip, git · Air-gap plan: download everything to USB if going fully offline |
| Vision Models | YOLO and SSD for people counting, PPE detection, defect monitoring |
| Speech & Audio | Vosk and Whisper for wake-words (“Hey Doctor”) and offline transcription |
| Local Chat & LLM | Llama (4-bit quantized) for FAQs and private log summarisation |
| Optimisation Pipeline | Convert to ONNX → TensorRT engine with FP16/INT8 quantization → Benchmark with tegrastats |
| Data & Backup | SQLite (single) or PostgreSQL (multi) · Local USB / NAS backups · Ship Docker images via USB/LAN updates |
| Security | Disable unused ports · SSH with keys only · Auth on all dashboards · Log all admin actions |
| Pilot Budget | Design: $3K-$7K · Build: $8K-$25K · Maintenance: $300-$1K per month |
Built for sectors where data
cannot leave the premises
Healthcare & Clinics
Finance & Banking
Industrial & Manufacturing
Government & Defence
Ready to build private AI
on your premises?
NVIDIA Jetson-based edge AI is not about collecting gadgets. It is about building a practical, ethical, and resilient layer of intelligence inside your business. Talk to us about your first pilot.