Research for apps that understand people
Bayon's product work is grounded in a long-running investigation into semantics, perception, cognition, and the social structure of intelligent systems.
Research pillar
Semantic understanding
How meaning, context, intention, and reference can be represented explicitly enough for software to reason with them.
Research pillar
Perception primitives
The recurring structures people use to notice, compare, classify, and act on the world around them.
Research pillar
Society of mind
A model of intelligence as cooperating agents, roles, procedures, and internal social organization.
Research pillar
Human-compatible systems
Product patterns that make AI systems more understandable, controllable, and useful inside real workflows.
From research to product behavior
The research is practical: it informs how Bayon designs AI apps that collect context, model roles, expose controls, and fit into human workflows.