Type
Module
Module
Module
Industry
Productivity
Integrates with
AWS S3
AWS Cognito
AWS DynamoDB
AWS OpenSearch
Links
Overview
The solution is a cloud-based document management and search module that enables users to upload .pdf and .doc/.docx files through a simple web interface. Once uploaded, files are stored in AWS S3 and processed asynchronously using AWS SQS. The backend listens to the queue, extracts text content from each file, and indexes it into AWS OpenSearch to enable full-text search with highlights. Users can then list, search, and delete their documents via API endpoints. The system is built using React/Next.js for the frontend and Express/Nest.js for the backend, with PostgreSQL or MongoDB for metadata storage. The architecture is designed to be cost-efficient, modular, and scalable for production deployment.
Problem
Many organizations accumulate a large number of PDF and Word documents across teams, but lack an efficient way to store, organize, and search through them. Traditional file storage solutions don’t offer text extraction, full-text search, or scalable indexing capabilities. As a result, employees waste time locating the right files or specific content within them, leading to productivity loss, poor data accessibility, and duplicated work. This challenge becomes even greater as the volume of documents grows over time.
Solution
We built a cloud-native document upload and search module where files are uploaded via a web interface, stored in AWS S3, and processed asynchronously via AWS SQS. The backend extracts and indexes file content into AWS OpenSearch, enabling fast, highlighted search results. This system offers efficient document management with scalable infrastructure using React/Next.js, NestJS/Express, and PostgreSQL or MongoDB.
Features
Document Storage
Uploaded files are securely stored in AWS S3. Metadata such as filename, user email, upload date, and S3 link is saved in a database (PostgreSQL or MongoDB).
Text Extraction & Indexing
The backend extracts text from the uploaded PDF or Word file and indexes it into AWS OpenSearch, enabling fast and accurate content search
Document Search
Users can search across their documents using full-text search powered by OpenSearch. Search results include filenames and highlighted text snippets showing the match.
Document Management
Users can list their uploaded documents and delete any file. The delete action removes the file from S3, the database, and OpenSearch in one unified request.
Benefits
Plug-and-Play Integration
The module is fully self-contained and can be easily integrated into existing systems, eliminating the need to build document handling and search features from scratch.
Faster MVP Development
Teams can focus on core product logic while this module handles document uploads, parsing, indexing, and search drastically reducing time-to-market.
Production-Ready Architecture
Built with scalable AWS-native components (S3, SQS, OpenSearch), the module is ready for real-world deployment, avoiding the need for later rewrites or re-architecture.
Reusable Across Projects
The module is decoupled and configurable, allowing it to be reused across multiple client or internal projects with minimal customization effort.
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Questions &Â Answers
What is the purpose of this solution?
It allows users to upload PDF and Word files, which are stored, processed, and indexed for fast full-text search, making document management easy and efficient.
How are files stored?
Files are uploaded via pre-signed URLs directly to an AWS S3 bucket. Metadata is stored in a database (PostgreSQL or MongoDB).
How is text extracted from documents?
A backend service reads files from S3, extracts text using libraries like pdf-parse or mammoth, and sends the content to AWS OpenSearch.
Can users search within documents?
Yes, users can perform full-text searches across uploaded documents. Results include highlighted text snippets showing exactly where the match occurred.
What happens after a file is uploaded?
S3 sends a notification to AWS SQS. The backend then processes the file, extracts text, and indexes it for search.
Can users manage their documents?
Yes, users can list all their uploaded files and delete any of them. Deleting a document removes it from S3, the database, and OpenSearch.
Is this solution scalable?
Yes. The architecture is modular and cloud-native. It can scale easily with AWS Lambda, RDS, and other services if needed.
How can this be deployed?
The backend and database can be containerized with Docker and deployed on AWS EC2. Alternatively, Supabase can be used for managed Postgres hosting.
Is This the Right Solution for You?
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Customer Ratings &Â Reviews
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5
June 25, 2025
Setup was painless, and the search experience is lightning fast.
