confidence-system

What problem does it solve?

Calibrates and communicates the trustworthiness of extraction and verification results across document pipelines, enabling targeted reviews and quality control.

Core Features & Use Cases

• Multi-signal confidence scoring combining method priors, source-text match, historical accuracy, edge-case distance, format conformance, and outlier checks.
• Calibration and thresholding to map confidence scores to review actions and QC sampling plans.
• Integration with pipelines to attach confidence and signals to extraction results and decision results.
• Use case: Allocate QC resources across thousand documents to minimize errors while controlling costs.

Quick Start

Configure an initial confidence model by mapping the core signals to a baseline score and wire it into the extraction/verification workflow.