Emotionally Intelligent AI
SOHMA enables AI systems to interpret human interaction dynamics and adapt behaviour in real time.
By modelling behavioural signals such as hesitation, pacing, engagement, and recovery, SOHMA provides a structured layer that guides how AI systems respond across digital environments.
From Human Interaction to Behavioural AI Systems
The framework connects interaction data, behavioural interpretation, and adaptive response orchestration into a unified system layer.
Transforming human interaction into behavioural signals that power adaptive AI systems
Human Interaction
Users engage with AI systems across games, learning platforms, wellbeing tools, and conversational environments.
Behavioural Signals
Interaction produces signals such as hesitation, pacing, engagement, disengagement, escalation, and recovery.
SOHMA Layer
Signals are structured into interpretable indicators that represent behavioural and emotional context.
Adaptive Behaviour
AI systems adjust pacing, support, challenge, and interaction style in response to behavioural context.
Behavioural Intelligence Layer
SOHMA processes behavioural signals such as hesitation, pacing, engagement, disengagement, and recovery patterns to build real-time understanding of user state.
These signals are structured into interpretable outputs that can be used by AI systems to adapt responses, adjust difficulty, or trigger interventions.
Infrastructure for AI Systems
SOHMA acts as an infrastructure layer that sits between user interaction and AI decision-making.
It enables developers to integrate behavioural intelligence into existing systems without modifying core models, providing structured signals, control layers, and transparent outputs.
Building the layer that makes AI responses safe, intelligent, and human-aware
