Openflows treats intelligence as circulation rather than possession.
Where many systems store knowledge as static content, Openflows is organized around movement: signals arrive from multiple sources, patterns stabilize briefly, people converge to reframe what matters, and outputs return as usable fragments.
Primary functions
Signal intake
Inputs are captured from observation, dialogue, research, and lived experience. Incomplete contributions are valid. The system accepts uncertainty and tracks weak signals before they disappear.
Pattern mediation (AI as infrastructure)
AI assists with clustering, summarizing, mapping, and recall. Mediation is explicit: when AI shapes an artifact, the process records how it was used, what humans changed, and what the tool could not assess.
Embodied convergence
Physical gatherings handle tasks digital systems do poorly: emotional calibration, disagreement without spectacle, co-regulation, and collective reframing. The body is treated as a cognitive instrument.
Redistribution
Outputs are designed to circulate rather than conclude: short notes, questions, tension maps, and actionable fragments that move into other contexts without requiring the full session.
Openflows does not centralize authority. It maintains conditions for collective cognition to persist across time, place, and mediation layers.