top of page

How to Build a Scalable Email Parsing System for Automated Data Extraction

Discover how MeltStudio built a scalable email parsing system to extract purchase data from inboxes, boosting app utility and user satisfaction.

1 Minutes Read

Challenge: Automated Email Parsing and Data Extraction


Building a robust, scalable email parsing system that could automatically scan users’ inboxes and extract complex purchase data from a variety of retailers was key to the client’s product offering.

The challenge was to develop an algorithm that could accurately detect and extract relevant information like receipts, product names, quantities, and purchase dates from diverse email formats while ensuring seamless integration into the app’s database.


 

​Solution

We built a scalable email parsing system by integrating the Gmail API with Firebase Cloud Functions, enabling secure and efficient email data extraction.


Using pattern-matching algorithms, we identified and structured purchase details like receipts, product names, and dates. Data was synchronized in Firebase for real-time access to the app, ensuring seamless integration.

The system’s architecture was designed for scalability, handling increased email volumes, and adapting to new retailer formats. Error-handling mechanisms ensured reliability, making the solution robust and future-ready.

​​​

The Outcome:​ The app now supports an ever-growing list of retailers, allowing users to track multiple orders efficiently, improving overall user satisfaction and app utility.


💡 At MeltStudio, we’ve mastered building scalable solutions like automated email parsing systems that simplify data extraction and enhance user experiences.


If you’re facing similar challenges or need a reliable partner to bring your tech vision to life, let’s talk!




Schedule today, and let’s create something exceptional together!

CONTINUE THE JOURNEY

The startup's Guide

Our blog provides step-by-step guides on selecting the best Tech Stack for your StartUp, building cost-effective teams, and more...

Geolocation App and Routing Algorithms for Reverse Logistics: Startup Challenges

Geolocation App and Routing Algorithms for Reverse Logistics: Startup Challenges

We developed a React Native App that improved last-mile logistics with smart geo-location algorithms for e-commerce businesses.

How to Develop a Scalable Queued System for Bulk Email Processing

We build an scalable queued system for processing high volumes of emails in e-commerce returns optimizing user experience through React Native solutions.

Building an Automated Returns System That Cuts Costs: Label Integration Case Study

Building an Automated Returns System That Cuts Costs: Label Integration Case Study

Automate return label system for e-commerce returns management, helping startups scale efficiently while reducing operational costs through seamless carrier integration and smart automation.

Tech Stack Choices: Ready-Made vs. Custom Ingredients for SaaS Strartups Success.

In SaaS, speed matters. Why "grow every ingredient" when quality ready-made tools get you to market faster? Analogy explained

bottom of page