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Document AI · Client project

DataSwitch: an AI document extraction platform we built for a client

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.

Client
DataSwitch
Built with
  • FastAPI (Python)
  • VLLM
  • PostgreSQL
  • React 19
DataSwitch: an AI document extraction platform we built for a client

What we built: AI that classifies documents and extracts their data

In short. DataSwitch is a document automation platform we built for a client. Users upload PDFs and images one at a time or in bulk; the platform classifies each document, extracts its data and returns structured, checkable output. It runs on FastAPI, vLLM, PostgreSQL and React.

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

DataSwitch: an AI document extraction platform we built for a client – picture 1

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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 


Screens from the platform


DataSwitch: an AI document extraction platform we built for a client – picture 2



DataSwitch: an AI document extraction platform we built for a client – picture 3



DataSwitch: an AI document extraction platform we built for a client – picture 4



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. 


Want a Web Solution for Business           Request a Quote 

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Questions about this project

Is DataSwitch a Prilient product?

No. DataSwitch is a platform we built for a client. Prilient's own products are Prilient AI Agents, VyapaarSense and Tainaat WorkforceOS.

Can you build something similar for our documents?

Yes. Our intelligent document processing work starts with a test on a sample of your own documents, then builds the pipeline around your document types and the systems the data has to reach.

Have a project like this in mind?

Tell us what you want to build. We'll show you similar work and how we'd approach yours.

NDA on request