Dynamic AI routing applies intelligent multi-LLM orchestration across 41 algorithms organized in 9 tiers — automatically selecting the optimal model and voting method for each task in under 50ms, reducing cost by up to 60% compared to fixed single-model deployments.
Dynamic AI Routing
Intelligent Multi-LLM routing across 41 algorithms and 7 specialized AI models — from intent parsing to self-evolving orchestration. Sub-50ms with 60% cost savings.
Why Dynamic Routing Matters
Static model assignment wastes resources and limits quality. Dynamic routing ensures every task gets the optimal AI model.
Sub-50ms Routing
Intent classification and model selection in under 50 milliseconds — faster than traditional API gateway routing.
Cost-Optimized
Automatically routes simple queries to cheaper models and complex tasks to premium models — reducing API costs by up to 60%.
Multi-LLM Orchestration
Coordinate multiple LLMs working in parallel or sequence — each handling the subtask it's best suited for.
Self-Evolving
The routing system learns from outcomes and continuously improves model selection accuracy through meta-learning.
9 Tiers of Algorithm Intelligence
41 algorithms organized into 9 tiers — from foundational operations to self-evolving meta-intelligence.
Supervisor
System-level orchestration and resource management
Foundation
Core intent parsing and basic NLP operations
Analysis
Deep semantic analysis and context extraction
Reasoning
Logical inference and chain-of-thought processing
Synthesis
Multi-source data integration and synthesis
Verification
Cross-validation and fact-checking mechanisms
Optimization
Performance tuning and cost optimization
Adaptation
Dynamic model selection and routing adaptation
Evolution
Self-evolving orchestration and meta-learning
HexaCore — The 7-Model Roster
3 Western : 3 Eastern : 1 Regional — balanced global intelligence, including Typhoon G38 powered by SCB10X for Thai-language sovereignty.
4 Consensus Methods
JITNA selects the voting method based on task criticality — from fast majority polling to SignedAI's 75% unanimous consensus.
Simple majority — fastest consensus for standard tasks.
Models weighted by domain proficiency — specialist gets higher vote share.
Models rank each other's outputs — best answer by peer evaluation wins.
75% consensus required — highest trust, slowest, used for critical SignedAI verification.
Explore Related Solutions
Related Resources
JITNA RFC-001 Protocol
The universal AI intent communication protocol — the HTTP of agentic AI that powers every routing decision.
Enterprise AI Memory
RCTDB persistent memory layer that gives routed models context-awareness across long-running sessions.
Regional AI
Routing orchestration for sovereign LLMs — Typhoon G38 and regional models selected by proficiency score.