Computational journalism, applied to commercial intelligence: verification before delivery, corrections on the record, and a visible chain from record to result.
AppliedXL checks each output against the underlying source before delivery. If the evidence does not support the claim, the item goes to review instead of publication.
Verifies: source authenticity, entity matching, extraction accuracy, timestamp consistency, event classification, evidence completeness.
Every probability is built from point-in-time history and measured against what actually happened. Every miss feeds calibration.
Tracks: historical backfill, point-in-time controls, outcome labels, calibration, backtests, model monitoring, false positives and negatives.
Before a forecast, market, or workflow goes live, the resolution rule is defined: which source decides, what counts as yes, by when, and how edge cases are handled.
Each resolution includes: authoritative source mapping, clear outcome logic, a timestamped settlement record, review and escalation.
When a source changes, an extraction fails, an entity match is corrected, or a forecast misses, the record is updated with a traceable history. The goal is not to hide uncertainty. The goal is to make the evidence, judgment, and correction path visible.
AppliedXL runs a secure editorial loop: AI reasons over records in context, through your editorial lens, with each step available for review.