Data delivered the moment it is observed, with minimal delay between an event in the world and its arrival at the systems that act on it.
Real-time data is information that reaches its consumer within moments of being observed, rather than being batched and shipped hours or a day later. The distinction is economic, not just technical: for a trading desk, a signal that everyone receives at the same time is worth far less than one that arrives first, and for a training pipeline, fresher inputs mean a model that reflects the world as it is now rather than as it was last quarter.
Delivering real time is a pipeline problem end to end. It means collecting close to the source, stamping each record with an event time at the edge, and streaming it out without waiting for a nightly job to run. The hard part is doing that at scale across thousands of noisy sources while keeping the latency budget small and the provenance intact - which is the whole design constraint EdgeOrigin is built around.
A live evaluation measures EdgeOrigin against your coverage requirements: decision-ready real-time data, delivery latency into your systems, and record-level provenance.