ToolsAugust 23, 2026via MarkTechPost
Building an End-to-End Document Intelligence Pipeline with deepDoctection
Why it matters
A practical engineering tutorial on building document intelligence pipelines—layout analysis, OCR, table extraction, and entity recognition—for practitioners scaling RAG systems. Useful reference for teams handling document ingestion at scale.
Key signals
- deepDoctection framework used for end-to-end pipeline
- Layout analysis, DocTR OCR, table extraction covered
- Custom entity recognition service implementation
- JSONL output for RAG workflows
- Document intelligence as applied tool (not model release)
- deepDoctection for layout analysis
- DocTR OCR integration
- Table extraction capability
- Custom entity recognition services
- End-to-end pipeline architecture
The hook
Deep dive: turning unstructured documents into RAG-ready structured data with deepDoctection.
Build an end-to-end document intelligence pipeline with deepDoctection. This tutorial covers configuring layout analysis, DocTR OCR, and table extraction, while demonstrating how to implement custom services for entity recognition and generate structured JSONL data for your RAG workflows.