Evaluation Mode lets you run ground-truth tests against your own labeled data and get back an F1 report, so you can validate accuracy on your actual document types before deploying a pipeline to production — rather than relying only on general benchmark numbers.

Primarily developer teams building document pipelines, RAG systems, or AI agents that need reliable structured output from documents — rather than back-office teams looking for a no-code review-and-approval workstation.

IDP Forge is a document AI platform built for developers who need to turn unstructured documents — PDFs, scans, forms, contracts — into structured, machine-usable data. It's built around a Parse API (document → structured JSON/markdown) and an Extract API (schema-based field extraction), with additional Split and Classify capabilities for routing mixed document batches.

Traditional IDP platforms are built around human review queues, validation workflows, and case management. IDP Forge is API-first: it's designed to be embedded directly into software and AI pipelines, with a developer-facing evaluation and confidence-scoring layer instead of manual review stations.

IDP Forge returns a confidence score for each extracted field, not just an overall document-level score. This lets you build auto-approval workflows where high-confidence fields pass through automatically and low-confidence fields get flagged for review.