The Comprehension Normalization Method For Networks
CNM is patented network analytics software that reveals the hidden causal structure behind complex systems. Originally developed for biological networks, CNM identifies functional subnetworks and underlying drivers that conventional clustering and surface-level analytics often miss. IIKONO is applying CNM across networks, language, and AI to uncover the logic beneath complex behavior.
Comprehension Normalization Method for Networks
Find What Really Drives the Network:
From genes to global systems, networks are shaped by layered causes. CNM untangles these hidden drivers, revealing functional subnetworks and the deeper architecture behind biological complexity, disease progression, and systemic behavior.
Comprehension Normalization Method for Language
Language is also a network. CNM for Language identifies shared meaning across different vocabularies, disciplines, and ways of expressing the same underlying idea. By using one language structure to reframe another, CNM helps reveal hidden conceptual connections across fields.
The Comprehension Normalization Method for AI
CNM in AI is at the intersection of Observability, Evals, and AI Safety. In AI CNM finds the underlying mechanisms behind the model's decision-making. Observable logic enables trust in the AI Model. When trusted AI can be used to its full potential even in highly regulated fields.
Awards & Accreditations
ELabNYC
First Growth Venture Capital (VentureCrush)
