Extraction Confidence Threshold

Extraction Confidence Threshold treats every automated document workflow as a two-tier system: fields the model extracts above a confidence cutoff flow straight through, and everything below it routes to a human queue. The framework matters because agencies sell document processing on time saved, yet the real cost driver is the review labor hidden behind low-confidence extractions. Instabase scores extracted fields with confidence values so teams can set that cutoff deliberately rather than accepting whatever the model returns. A practical setup: run a 200-document sample from a client's invoice or contract backlog, plot accuracy by confidence band, then price the retainer against the review hours the low band actually consumes. Superdocu's validation dashboards show the same principle on collection workflows, where missing or expired documents trigger automated reminders instead of staff chasing. Agencies that publish the threshold and the resulting review rate turn a vague accuracy claim into a defensible service-level commitment, which is what keeps document work from being priced like a commodity utility.