Multiple agents. One truth. We don't trust any single AI model. We make them check each other's work, and surface every discrepancy to your supervisors.
Every data point runs through independent AI agents. When they agree, you get validated extraction. When they diverge, even on a single field, the system stops and escalates.
Other vendors hide uncertainty behind confidence scores.
We surface it, so your supervisors can act.
Legal liability lives in the edge cases. When our consensus engine detects ambiguity, a blurred scan or conflicting data, it doesn't guess. It routes the specific data point to your analyst's Exception Queue.