Aurora
A cognitive architecture that routes reasoning across specialized inference pathways, achieving frontier performance through mechanism-first design.
Architectural Foundations
Aurora implements a cognitive pipeline that dynamically routes queries through specialized inference pathways. The system leverages tiered model deployment, adaptive memory systems, and multi-stage reasoning to optimize for both performance and computational efficiency.
Query Analysis
Cognitive load assessment and complexity scoring determine optimal routing strategy.
Tiered Routing
Dynamic dispatch to appropriate inference tier based on reasoning requirements.
Memory Integration
Contextual retrieval and working memory systems enhance reasoning depth.
Reasoning Synthesis
Multi-stage inference with verification and self-correction mechanisms.
Cognitive Routing: Aurora's Python Brain module analyzes query complexity in real-time, directing simple queries to efficient tiers while escalating complex reasoning tasks to frontier models. This mechanism-first approach reduces latency and cost without compromising capability.
Systemic Capabilities
Aurora integrates multiple cognitive subsystems to achieve robust performance across diverse reasoning tasks while maintaining efficiency and safety constraints.
Reasoning Depth
- Multi-stage inference with chain-of-thought integration
- Self-correction and verification mechanisms
- Context-aware reasoning path selection
Memory Systems
- Episodic memory retrieval for contextual awareness
- Working memory optimization for complex tasks
- Adaptive context window management
Safety Architecture
- Tiered content filtering and moderation
- Behavioral alignment monitoring
- Fallback routing for edge cases
Performance
- Dynamic tier selection based on query complexity
- 95% accuracy in routing classification
- 40-60% cost reduction through efficient dispatch
Evaluation Results
Performance across established benchmarks demonstrates frontier-competitive capability while maintaining operational efficiency through intelligent routing.
Operational Characteristics
Evaluation Context: All benchmarks were conducted using Aurora's standard routing configuration. Results represent averaged performance across multiple evaluation runs with consistent system parameters.