SignalGraph: A New Architecture for Enterprise Attention

Signal Labs CEO Rajeev Ronanki introduces SignalGraph™, a distributed blackboard architecture that treats signals, not data, as first-class primitives for enterprise decision-making.

When it comes to leaders making decisions, most enterprises don't have a lack of data. The shortage is in leadership attention. Through the power of AI, it’s being revealed that often, the most important signals to inform more effective and defensible decisions are actually buried within an enterprise’s data. Where there is no shared substrate for deciding which signals matter, and need to be delivered to the right people before the window to act closes.

Signal Labs CEO Rajeev Ronanki and Chief Architect Plamen Petrov, PhD published a new research paper formalizing SignalGraph™: a distributed blackboard-based architecture that treats signals as first-class computational primitives; and is augmented by an Equilibrium Engine to enforce information-theoretic constraints at every inference boundary. The research extends the thesis of Signal Labs' foundational white paper, where the constraint on institutional decision-making is not driven by data or models, but by the absence of a shared substrate for convening attention.

Read the paper:
SignalGraph: A Distributed Blackboard Architecture for Convening Enterprise Attention with Equilibrium-Governed Inference →