--- title: Document Processor emoji: ๐Ÿ  colorFrom: yellow colorTo: blue sdk: docker pinned: false --- # ๐Ÿฆ Appian Credit Union - Smart Document Processor AI ## ๐ŸŽฏ Problem Statement Appian Credit Union receives thousands of PDF documents daily that need to be classified, verified, and organized. Our solution automates this process using AI, significantly reducing manual effort and processing time. ## ๐Ÿ’ก Innovation Highlights - ๐Ÿค– Hierarchical document classification system - ๐Ÿ‘ค Intelligent person-document association - ๐Ÿ“Š Automated metadata extraction - ๐Ÿ”„ Batch processing capabilities - ๐ŸŽจ Modern, intuitive UI ## ๐ŸŽฏ Document Types Supported - ๐Ÿ’ณ Bank Account Applications - Credit Card Applications - Savings Account Applications - ๐Ÿชช Identity Documents - Driver's License - State/Country ID - Passport - ๐Ÿ“Š Financial Documents - Income Statements - Paystubs - Tax Returns - ๐Ÿงพ Receipts ## ๐Ÿ› ๏ธ Technical Architecture - **Backend Framework**: Python + Flask - **Document Processing**: PyPDF2 - **ML/AI Pipeline**: - TF-IDF Vectorization - Naive Bayes Classification - Named Entity Recognition - **Frontend**: HTML + JavaScript + Tailwind CSS - **Database**: SQLite - **Deployment**: Hugging Face Spaces ## โœจ Key Features ### 1. Hierarchical Classification - Person-level document association using: - Name matching - Government ID recognition - Email address extraction - Document type categorization - Automatic grouping of similar documents ### 2. Information Extraction - Automated extraction of: - Personal information - Financial data - Document dates - Account numbers - Government ID numbers ### 3. Processing Pipeline - Batch document upload - Real-time processing - Error handling and validation - Progress tracking - Results summary ## ๐Ÿš€ Getting Started ### Prerequisites ```bash Python 3.9+ pip Virtual Environment (recommended) ``` ### Installation 1. Clone the repository ```bash git clone https://github.com/yourusername/appian-document-processor.git cd appian-document-processor ``` 2. Install dependencies ```bash pip install -r requirements.txt ``` 3. Run the application ```bash python app.py ``` 4. Access at `http://localhost:7860` ## ๐Ÿ‘ฅ Team Members - Sanjay Malladi ## ๐Ÿ“ License MIT License ## ๐Ÿค Acknowledgments - Appian AI Challenge Team - IIT Madras - Open Source Community --- *Developed for the Appian AI Challenge 2024-25 at IIT Madras*