The Challenge
Before DocExtract Pro:
- Extracting fields like PO number, SLI codes, rates, quantities, delivery dates etc. from PDFs was painfully manual
- Many POs had non-standard layouts—copy-pasting into Excel often broke formatting
- Field-level precision (like mapping Rate to SLI Code) was hard to automate
- Analysts spent hours scanning & compiling this data line by line
The Solution: DocExtract Pro
We built a desktop app using PyQt6 that:
- Lets users upload multiple PDF files in one go
- Uses AI API to extract structured data with context
- Extracts both global fields (e.g., PO Number, Customer Name) and item-level details (e.g., SLI Code, Rate, Quantity)
- Converts everything into clean Excel format
- Features a sleek UI with dropdowns, logging, and custom query editing
DocExtract Pro is like having a data analyst that works in milliseconds.
Key Features
- Animated Interface with gradients, rounded layouts, and elegant fade-in dialogs
- PDF upload & deletion handled via secure API
- Intelligent field parsing using regex and AI prompts
- Users can customize the question sent to API for tailored extraction
- Exports structured tables ready for reporting in Excel
- Tracks all uploads with a source_ids.log file for audit and cleanup
Architecture at a Glance
- Frontend: (custom UI, modals, scroll areas, gradients)
- Backend: API for NLP-based PDF understanding
- Data Handling: Pandas for final Excel compilation
- Logging: Real-time QTextEdit console + .log file for backend traceability
The Impact
- 90% faster processing compared to manual entry
- Reduced human error to near-zero
- Supports multiple PDFs per run
- Easily extendable to other document types
- Ready for deployment in purchase, finance, or legal teams
Want to Integrate AI Extraction into Your Workflow?
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