OpenEnergiX
n/decision-graph · system

The decision graph

Not one graph — many graphs, dynamically connected. Any node can reach any node. The topology is learned, and the topology is the moat.

Many graphs, one reality

Every function already reasons in a graph. Commercial has one. Sourcing has one. Engineering, market intelligence, suppliers — each has a real internal structure that works. What breaks is what happens between them: the enterprise collapses rich graph state into single signals passed linearly down the line.

The information itself is the same information. Supplier capacity is one fact — yet today it lives as a separate, partial, differently-named node in four functional graphs, refreshed at different times, trusted to different degrees.

Dynamically connected

OpenEnergiX joins the graphs. Demand, specs, supplier capability, qualification, should-cost, capacity, lead time, negotiation, execution — connected across functions, not within silos. Context propagates through the joined structure the way it should: any node reachable from any node, collapsed into a single recommended action at decision time.

Distance is learned

Which nodes belong close together — engineering's qualification timing next to sourcing's supplier capability, not three handoffs away — is not knowable from an org chart. It is learned by operating inside the decisions. That learned topology is what makes each individual graph better the moment they connect.