AI companies are competing on model intelligence. We've solved the context architecture problem that makes AI useful for complex human decisions. This creates a new capability: contextual reasoning about weighted relationships between factors. That's a different market with less competition.
Current context engineering approaches treat context as information retrieval. But it's not Retrieval Augmented Generation (RAG) or fine-tuning prompts. Spherical Thinking treats context as weighted, interconnected factors with explicit relationships. This enables AI to reason about what drives decisions, not just what's mentioned. We've tested structured contextual mapping with 45,000+ people over 25 years, across 50+ unique applications, with transferability validated by 1,000+ professionals trained in high-stakes, mandated environments.