A document processing platform for extracting, organizing, and searching information from uploaded files.
DocuMind will focus on turning unstructured documents into structured, searchable data through automated processing and user-assisted validation.
- Document upload and management
- PDF text extraction
- OCR for scanned documents
- Document classification
- Structured field extraction
- Extraction confidence indicators
- Manual review and correction
- Full-text document search
- Processing history
- Structured data export
- Optional semantic search
| Layer | Technology |
|---|---|
| Backend | Python, FastAPI |
| Frontend | React, TypeScript |
| Database | PostgreSQL |
| Object Storage | MinIO |
| Cache | Redis |
| Processing | Python document and OCR libraries |
| Infrastructure | Docker, Docker Compose |
| CI/CD | GitHub Actions |
| Testing | pytest, Playwright |
DocuMind will use an asynchronous document processing pipeline.
Uploaded documents will be stored separately from application metadata. Background workers will perform extraction, classification, and structured data processing.
The architecture will emphasize:
- Safe file upload and validation
- Isolated document processing
- Asynchronous task execution
- Reproducible extraction results
- Structured output validation
- Traceability to source documents
- Protection of sensitive information
- Measurable extraction accuracy
AI-based extraction may be introduced where it provides a measurable improvement over deterministic approaches.
- Define document and extraction models
- Set up FastAPI and React
- Configure Docker, MinIO, and CI
- Implement document upload
- Add PDF text extraction
- Implement OCR processing
- Build asynchronous processing pipeline
- Implement structured data extraction
- Add review and correction interface
- Implement search and export
- Evaluate extraction quality and security
Planning
The initial document processing scope has been defined. Implementation has not started.
License to be determined.