This project presents one application direction of the IARIP research architecture. The presented model is currently in the research and pilot validation phase. The timelines below outline the expected validation and development steps of the IARIP research architecture across different application domains. Following research validation, IARIP aims to initiate real-world projects together with industry and market partners based on the successfully validated models.

Energy-Efficient Edge AI Unit for Local LLM Inference and Real-Time Intelligence

The AVA Node is a compact, high-efficiency edge-level AI server designed for running large language models and real-time AI workloads with significantly reduced energy consumption.

It represents the physical execution unit of the AVA Resonant Intelligence architecture — combining optimized hardware with a resonance-based software stack to deliver measurable efficiency gains over conventional AI inference systems.

The challenge

Running modern AI models typically requires:

• – high GPU power consumption,
• – constant cloud connectivity,
• – and centralized infrastructure with rising operational costs.

For many enterprise, governmental, industrial, and privacy-sensitive environments, this model is:

• – too expensive,
• – too energy-intensive, or
• – simply not permitted.

The solution – AVA Node

The AVA Node provides a local, energy-optimized AI execution unit that:

• – runs LLMs and AI models on-site,
• – minimizes energy and compute waste through resonant optimization,
• – operates independently of cloud infrastructure.

It is not a general-purpose server, but a purpose-built AI node optimized for efficient inference.

Hardware architecture

The AVA Node integrates a balanced, energy-aware hardware stack:

• – optimized GPU / NPU for inference workloads
• – low-power CPU for orchestration and control
• – high-bandwidth memory
• – NVMe-based storage
• – quiet, energy-efficient cooling
• – industrial-grade, 24/7-ready design

The hardware is selected and tuned specifically for sustained AI inference at low power cost.

Software stack

Each AVA Node runs the full Resonant Optimization Suite:

• – RCF-LIM – LLM inference optimization
• – HGO – intelligent GPU–CPU workload distribution
• – ADC-Optim – energy-aware system operation
• – RCF-Secure – built-in security and anomaly detection

The system dynamically adapts execution strategies based on workload patterns, activating only the compute resources that are actually required.

Key benefits

• – Local AI execution without cloud dependency
• – 30–40% reduction in energy and compute usage
• – optimized specifically for LLM inference
• – low-latency, real-time responses
• – full data privacy and on-site control
• – stable 24/7 operation
• – scalable from a single unit to large node clusters

Deployment scenarios

• – enterprise AI assistants running locally
• – healthcare, education, and government systems
• – industrial automation and IoT environments
• – energy and smart-grid infrastructure
• – research institutions and laboratories
• – decentralized and mobile AI networks

How it fits into the AVA ecosystem

The AVA Node is the physical foundation of the Resonant Intelligence architecture:

• – runs AVA Core locally,
• – executes all resonant optimization modules,
• – connects into RI-Net for distributed intelligence,
• – enables private, decentralized AI infrastructures.

Project status

• – ready-to-start hardware project
• – specification defined and pilot-capable
• – suitable for rapid prototyping
• – low integration risk
• – immediately addressable edge-AI market

AVA Node turns Resonant Intelligence into a tangible system — a measurable, deployable, and energy-efficient AI unit designed for real-world operation.