Techmetascore Backend

Developed Techmetascore Backend – Building User Engagement and Secure Interactions

Techmetascore’s backend is where things get exciting. The platform's core is built to let users not only browse and review products but also interact with each other in a way that feels natural and seamless.

Authentication & Security

The first big feature was setting up the authentication system. Users can easily sign up, log in, reset passwords, change their credentials, and even verify their email to ensure their account is secure. To keep things modern, Firebase Auth was integrated, allowing users to log in using Google, Facebook, or other providers, making it quick and simple. But security was the real priority here—I implemented JWT (JSON Web Tokens) with cipher encryption algorithms, ensuring that all user information is fully protected. The goal was to keep user data safe, even with heavy interaction.

Feed & Posting System

Think of it like Twitter for reviews. Users can read through a dynamic feed that pulls in reviews, comments, and posts from others. Posting a review involves not just text but also a rating system where users score the product. And it doesn’t stop there—other users can comment on reviews, reply to comments, and engage in conversations about the products they care about. It’s all designed to feel smooth and connected, encouraging interaction without slowing down the experience.

Likes/Dislikes, Follow, & Notification System

A like/dislike system similar to Reddit’s voting model is in place. Users can upvote or downvote a review, comment, or reply, which helps surface the best content. To add a layer of social interaction, users can follow each other, seeing posts from those they care about in their feed. Notifications were also a must—whenever someone comments on your post, replies to a comment, or follows you, the notification system kicks in, keeping users updated in real-time.

Rating Products & Brands

The core of Techmetascore is aggregating ratings for products and brands, and I built out a system that does just that. Each review contributes to a product’s overall rating, and brand ratings are calculated based on their products’ performances. It’s designed to be flexible, so it easily scales as more products and reviews come in.

Search Functionality

The platform also needed a powerful search feature, so I developed a system where users can search for both other users and products. It’s not just about finding the right person or product—it’s about making sure those search results are accurate and relevant, so users don’t have to scroll endlessly to find what they need.