Definition
The execution of LLM inference and RAG indexing directly on localized hardware or on-device environments, eliminating reliance on centralized cloud APIs. This architecture prioritizes data sovereignty and near-zero latency by processing proprietary information within the local network perimeter, though it requires significant model quantization to fit hardware constraints.
On-device AI processing vs. Cloud API consumption.
"A personal chef working in your private kitchen versus ordering takeout from a central restaurant."
- Quantization(Prerequisite)
- Local LLM(Component)
- Data Sovereignty(Benefit)
- Vector Database (Embedded)(Component)
Conceptual Overview
The execution of LLM inference and RAG indexing directly on localized hardware or on-device environments, eliminating reliance on centralized cloud APIs. This architecture prioritizes data sovereignty and near-zero latency by processing proprietary information within the local network perimeter, though it requires significant model quantization to fit hardware constraints.
Disambiguation
On-device AI processing vs. Cloud API consumption.
Visual Analog
A personal chef working in your private kitchen versus ordering takeout from a central restaurant.