Docling
Overview
Docling is an open-source document understanding framework designed to extract structured content from complex files such as PDFs, reports, and business documents. It helps convert unstructured documents into clean, machine-readable formats that can be used for downstream NLP and document AI workflows. By integrating Docling with Label Studio, teams can evaluate model outputs, collect human feedback, and build high-quality labeled datasets to improve document extraction and understanding performance over time.
Benefits
- Accelerated document AI workflows: Pre-process and extract structured content from raw PDFs and documents.
- Human-in-the-loop evaluation: Use Label Studio to review and validate Docling model outputs for accuracy and consistency.
- Better training and fine-tuning data: Create labeled benchmarks and datasets to fine-tune Docling models for domain-specific documents.
- Improved extraction quality: Capture corrections and edge cases directly from annotators to strengthen model performance.
- Flexible integration: Support a wide range of document understanding tasks, including layout analysis, text extraction, and structured data labeling.
