PDF to Sales Order Automation System

This project aims to develop a custom Frappe application that automates the conversion of PDF purchase orders into Sales Orders in ERPNext. The system will eliminate manual data entry, reduce processing time, and minimize errors by automatically extracting customer information, item details, quantities, and pricing from uploaded PDF documents and creating validated Sales Orders. Reduce sales order processing time by 70-80% Eliminate manual data entry errors Enable faster order fulfillment and improved customer satisfaction Process multiple PDF formats from different customers Maintain accurate audit trails for all automated transactions Project Scope In Scope Custom Frappe app development for PDF processing ​ PDF text extraction and OCR capabilities for scanned documents Data validation and verification workflows Automated Sales Order creation with field mapping ​ User interface for PDF upload, preview, and manual corrections Error handling and logging mechanisms Support for multiple PDF templates and layouts Integration with existing ERPNext Customer and Item masters Out of Scope Modifications to core ERPNext Sales Order functionality Integration with external email systems for automatic PDF retrieval Invoice processing or other document types Customer portal development Mobile application development Technical Requirements System Components 1. PDF Upload Module DocType to manage PDF file uploads File validation and storage Batch processing capability Status tracking (Uploaded, Processing, Completed, Failed) 2. PDF Parser Engine PyMuPDF for native PDF text extraction Tesseract OCR for scanned documents pdfplumber for table extraction Custom parsing logic for different PDF templates 3. Data Extraction Layer Extract customer information (name, address, contact) Parse item details (code, description, quantity, unit price) Identify dates (order date, delivery date, PO number) Extract tax and discount information Calculate totals and validate against PDF values 4. Validation Engine Verify customer exists or flag for creation Validate item codes against Item master Check pricing against Price Lists Verify tax rates and applicability Flag discrepancies for manual review ​ 5. Mapping Configuration Configurable field mapping interface Support for customer-specific PDF templates Default mapping rules with override capability Regular expression patterns for data extraction 6. Sales Order Creation Module Automated Sales Order generation Pre-population of all required fields Tax calculation and application Workflow submission based on approval rules ​ 7. User Interface Dashboard showing processing statistics PDF upload interface with drag-and-drop Extracted data preview and editing screen Error resolution interface Bulk processing queue management Field Mapping Specifications Customer Information Mapping PDF Field Sales Order Field Validation Bill To Name customer Must exist in Customer master Ship To Address shipping_address_name Create if not exists Customer PO Number po_no Alphanumeric validation Order Date transaction_date Date format validation Delivery Date delivery_date Must be future date Item Details Mapping PDF Field Sales Order Field Validation Item Code/SKU item_code Must exist in Item master Description item_name Auto-populate from Item Quantity qty Numeric, greater than 0 Unit Price rate Numeric, validate against Price List Discount % discount_percentage 0-100 range Tax Code item_tax_template Validate tax template exists Document Level Mapping PDF Field Sales Order Field Validation Total Amount grand_total Calculate and compare Tax Amount total_taxes_and_charges Calculate from items Currency currency ISO currency code Payment Terms payment_terms_template Validate template exists ​ Technical Stack Backend Frappe Framework (Python) PyMuPDF (fitz) for PDF parsing Tesseract OCR for image-based PDFs pdfplumber for structured data extraction Regular expressions for pattern matching Frontend Frappe's built-in UI components Custom JavaScript for interactive features Vue.js for complex UI elements Database MariaDB (Frappe default) Custom DocTypes for app-specific data Success Metrics Performance Metrics PDF processing time: < 30 seconds per document Data extraction accuracy: > 95% Successful Sales Order creation rate: > 90% System uptime: 99.5% Business Metrics Reduction in order processing time: 70%+ Error rate reduction: 80%+ User adoption rate: 90% within 3 months ROI achievement within 6 months ​ Risk Management Technical Risks Risk: Varying PDF formats may not parse correctly Mitigation: Build template library and regex pattern configuration; implement manual override capability Risk: OCR accuracy issues with poor quality scans Mitigation: Implement confidence scoring; flag low-confidence extractions for manual review Risk: Performance degradation with large PDFs Mitigation: Implement background job processing; add file size limits and optimization Business Risks Risk: User resistance to automated system Mitigation: Provide comprehensive training; implement gradual rollout with pilot users Risk: Integration issues with custom ERPNext modifications Mitigation: Conduct thorough environment analysis pre-development; maintain staging environment ​ Infrastructure Development and staging servers OCR processing resources PDF storage allocation Third-Party Services Tesseract OCR (open source) Python libraries (open source) Cloud storage for PDF files ​ Post-Implementation Support Training Administrator training (2 sessions) End-user training materials Video tutorials and documentation Maintenance 90-day warranty period for bug fixes Monthly maintenance and updates Feature enhancement roadmap 24/7 critical issue support ​ Assumptions ERPNext instance is properly configured with Customer and Item masters PDF documents follow relatively consistent formats per customer Users have basic ERPNext knowledge Network connectivity and server resources are adequate Frappe framework version compatibility is maintained ​ Next Steps Project Kickoff Meeting: Review requirements and finalize scope Environment Setup: Prepare development, staging, and production environments PDF Sample Collection: Gather representative PDF samples from all customers Technical Design Review: Finalize architecture and integration approach Development Sprint Planning: Break down deliverables into 2-week sprints ​ Prepared using Claude Sonnet 4.5 Related How to implement PDF parsing in Frappe custom app Sample code for extracting Sales Order data from PDF ERPNext Sales Order fields to map from PDF Best OCR libraries for PDF invoice extraction in Python Testing checklist for PDF to Sales Order feature

Projektin tunnus (ID): 40194482