Document Intelligence Review — Page 3

Pre-trained models excel on standard documents.

Per-field SLAs hold vendors accountable for the extractions that actually matter to buyers.

Per-page rates hide mode selection costs that can inflate bills by four times or more.

IDP and agentic AI serve different workflow layers, not the same job.

Flawed ground truth undermines every accuracy claim that follows it.

Turning human corrections into training data improves extraction accuracy where it matters most.

Confidence scoring and exception routing replace blanket human review.

Confidence scores mean nothing without calibration to match them to real accuracy.

A single misclassification corrupts an entire IDP pipeline silently.

These three tools solve different problems in sequence, not three ways to do the same job.