AURA AI
Intelligent LLM Orchestration
AURA AI intelligently orchestrates LLM workloads and inference traffic across distributed compute layers.
It dynamically routes requests to the optimal model, node, or context layer based on latency,
cost, and task complexity — ensuring performance, efficiency, and reliability at scale.
How AURA AI Works
Enterprise-grade LLM orchestration, explained simply
Dynamic Model Distribution
Distributes inference requests across models and nodes balancing latency, throughput, and cost while honoring constraints.
Allows for larger models to be housed through a cluster of nodes.
Intelligent Routing
Inference traffic is smartly directed using context and hardware profiles. Specific models can be assigned to particular nodes based on requirements.
Multi-Model Awareness
Keeps track of multiple models across different domains, each with its own optimized model. The routing engine ensures domain isolation, data security, and performance on shared infrastructure.
Key Features
Advanced capabilities for enterprise AI infrastructure
Performance Optimization
Automatically routes requests to the fastest available model for each specific task type, minimizing latency while maximizing throughput.
Cost Efficiency
Intelligently uses smaller, cheaper models for simple tasks and reserves powerful models for complex operations, reducing overall compute costs.
Auto-Scaling
Dynamically scales compute resources up or down based on demand, ensuring optimal performance during peak loads and cost savings during quiet periods.
Security & Isolation
Maintains strict data isolation between different domains and models while ensuring all processing stays within your secure infrastructure.
Ready to Orchestrate Your AI Infrastructure?
Let AURA AI optimize your LLM workloads for maximum performance and efficiency.