DataSwitch
DataSwitch: Data Extraction Platform
An AI-based document automation platform to eliminate manual data entry, reduce errors, and enable organizations to extract meaningful insights from unstructured documents with speed and precision.
Technologies Used
The Ultimate Document Extraction Platform Powered by AI
DataSwitch is a powerful document automation platform to simplify how businesses handle large volumes of documents. It allows users to upload PDFs, images, or PNG and automatically processes them using intelligent classification
Key Features of DataSwitch
Drag-and-drop document upload (single & bulk)
AI-based document classification
Automated data extraction from documents
High-speed processing for large datasets
Support for PDFs, images, and PNG files
Structured output for easy data validation
Secure and reliable data handling
Project Dashboard
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Project Objective
Design a clean and intuitive interface for easy document uploads via drag-and-drop or file explorer
Integrate AI-based document classification to identify different document types automatically
Develop advanced data extraction pipelines to capture relevant fields from documents
Build a robust backend architecture to handle bulk processing efficiently
Project Timeline
Phase 1 (Planning & Research): Requirement analysis and architecture planning
Phase 2 (Design): UI/UX design and workflow mapping
Phase 3 (Development): Core platform development and AI integration
Phase 4 (Testing): Performance testing and accuracy validation
Phase 5 (Deployment): Final launch and optimization
Technological Integration
Backend
Framework: FastAPI (Python)
Database: PostgreSQL, Redis
AI/ML: VLLM, Hugging Face, PyTorch
Frontend
Framework: React 19 (TypeScript)
Build Tool: Vite
Styling: Tailwind CSS 4
Routing: React Router DOM v7
HTTP Client: Axios
How Website Look: Watch the Glimpses
Summing Up
DataSwitch successfully enabled organizations to automate document processing, save time, and make better data-driven decisions.
All the beneficiaries who have used this tool experienced faster processing of large volumes of documents and enhanced operational efficiency.
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