Hexanet's two-stage hybrid pipeline combines the precision of small language models with the reasoning power of large language models, orchestrated by our proprietary Statistical Inference Network.
Precision retrieval meets expressive reasoning
High-precision extraction from structured data sources
Expressive outputs grounded in retrieved data
Deep dive into Hexanet's technical architecture
Proprietary probabilistic reasoning system at the core of Hexanet
Precision retrieval layer for high-accuracy data extraction
Expressive reasoning layer for natural language generation
High-dimensional embeddings for semantic search and retrieval
Network of relationships connecting concepts and entities
Entropy-based question generation and sequencing
Maximum information gain through uncertainty reduction
Real-time probability assessment and validation
Multi-dimensional concept space for relationship analysis
A 7-step hybrid pipeline combining neural retrieval with statistical inference
Ingest verified sources: research papers, medical references, CDC, Wikipedia medical pages, and clinical guidelines.
Condition–symptom–term–treatment relations designed around how humans connect ideas.
Multilingual embeddings with structured schemas for precise retrieval.
High-precision extraction, terminology alignment, normalization, and field mapping.
Real-world metrics from production deployments
Experience the power of our hybrid AI architecture through interactive demos