Our proprietary mathematical approach to creating the world's most intelligent multi-model AI system.
The Enhanced Language Processing Allocator (Elpa) represents our most advanced research in AI routing systems. This proprietary technology uses a sophisticated mathematical scoring system to direct user queries to the most suitable Large Language Model based on intent, complexity, and sensitivity.
Extracts and quantifies intent, complexity, and sensitivity from user queries using advanced NLP techniques.
Maintains detailed capability profiles for each LLM with numerical affinity scores across multiple dimensions.
Applies a weighted mathematical formula to compute optimal model selection based on query characteristics.
strength = min(1, matches * 0.5)Each intent is scored from 0 to 1 based on keyword matches in the query.
Score = Σ(In * αn,m) + (C * βm) + (S * γm) + φm(...)Multi-dimensional representation of query intents with proprietary weighting coefficients
Non-linear complexity evaluation using our patented depth estimation algorithm
Additional confidential factors that enhance routing precision (represented by φ)
The complete Elpa routing algorithm contains additional proprietary components and weighting factors that are not publicly disclosed. The mathematical representation shown above is a simplified version of our actual implementation.
Our proprietary LLM capability matrix contains detailed performance metrics across multiple dimensions. The actual values used in our production system are continuously updated based on model performance and are confidential.
Note: The full capability matrix includes dozens of additional dimensions and proprietary metrics that are continuously updated through our evaluation pipeline.
Unlike conventional routing systems that rely on simple keyword matching or basic classification, Elpa employs a sophisticated mathematical scoring system that precisely quantifies the suitability of each LLM for a given query. This approach ensures optimal task assignment while maintaining safety guardrails for sensitive content.
The algorithm's flexibility allows us to easily adjust LLM profiles as capabilities evolve, ensuring our system continuously improves and adapts to new models and use cases.
For complex queries that span multiple domains or require specialized capabilities, Elpa can orchestrate multiple models to work together, leveraging the strengths of each.
Handles code generation for React components and data processing functions due to its strong coding capabilities.
Provides detailed explanations of the code and concepts due to its strength in clear communication.
Optimizes data visualization algorithms due to its mathematical expertise.
Claude generates core React components and data processing functions
DeepSeek optimizes data visualization algorithms and statistical functions
Claude integrates the optimized algorithms into the codebase
GPT-4o provides detailed explanations of the code and concepts
Handles information gathering and initial analysis due to its broad knowledge base.
Analyzes technical details and mathematical concepts due to its expertise in scientific domains.
Creates the final summary and accessible explanations due to its strength in writing and communication.
Multiple models cross-validate information for higher factual accuracy
Each model contributes its unique strengths to different aspects of the task
Technical depth combined with accessible explanations for diverse audiences