Concept / Multimodal extraction & grounded review

DocuMind · Document Intelligence

A document intelligence pipeline for mixed-layout PDFs, tables, forms, and Nepali–English content with source-level verification.

Computer VisionLLMs & NLPAutomation

The question.

Document extraction fails when a plausible field value loses its page position, table context, or connection to the original evidence.

The architecture combines layout-aware extraction with schema validation and a review queue for uncertain or inconsistent fields.

The proposed approach.

  • Parse text, layout, tables, and image regions while preserving page coordinates
  • Extract into explicit typed schemas with field-level source references
  • Check totals, required fields, and cross-document consistency
  • Send uncertain outputs to a reviewer with the relevant source region

Target architecture.

PDF / imageLayout and OCRStructured extractionValidationEvidence-linked reviewExport

The difficult parts.

  • Complex tables and scanned documents
  • Code-switching and numeric formatting
  • Distinguishing a missing value from a guessed one

How to evaluate it.

  • Field and table accuracy by document family
  • Source-coordinate correctness and confidence calibration
  • Review effort and correction rate

Planned deliverables.

  • A document and extraction schema collection
  • An evidence-linked review workflow
  • A document-family evaluation protocol

Design principles.

A missing value is better than a confident invention.
Keep extracted facts connected to their original page.